Triple
T4422236
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kristin Lavransdatter |
E95126
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Kristin
Kristin is the central female protagonist of Sigrid Undset’s historical novel trilogy "Kristin Lavransdatter," set in medieval Norway.
|
E437279
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Kristin | Statement: [Kristin Lavransdatter, givenName, Kristin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kristin Context triple: [Kristin Lavransdatter, givenName, Kristin]
-
A.
Kristin
Kristin is one of the official mascots of the 1994 Winter Olympics held in Lillehammer, Norway.
-
B.
Kristin
Kristin is the given name of the acclaimed British-French actress Kristin Scott Thomas, known for her roles in films such as "The English Patient" and "Four Weddings and a Funeral."
-
C.
Kristen
Kristen is a central female character in the romantic comedy film "Think Like a Man," whose love life and personal growth are explored through the movie’s ensemble relationship dynamics.
-
D.
Kristen
Kristen is the birth name of Kris Jenner, the American television personality and matriarch of the Kardashian–Jenner family.
-
E.
Kristen
Kristen is a feminine given name commonly used in English-speaking countries, often associated with notable figures in entertainment and public life.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Kristin Triple: [Kristin Lavransdatter, givenName, Kristin]
Generated description
Kristin is the central female protagonist of Sigrid Undset’s historical novel trilogy "Kristin Lavransdatter," set in medieval Norway.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kristin Target entity description: Kristin is the central female protagonist of Sigrid Undset’s historical novel trilogy "Kristin Lavransdatter," set in medieval Norway.
-
A.
Kristin
Kristin is one of the official mascots of the 1994 Winter Olympics held in Lillehammer, Norway.
-
B.
Kristin
Kristin is the given name of the acclaimed British-French actress Kristin Scott Thomas, known for her roles in films such as "The English Patient" and "Four Weddings and a Funeral."
-
C.
Kristen
Kristen is a central female character in the romantic comedy film "Think Like a Man," whose love life and personal growth are explored through the movie’s ensemble relationship dynamics.
-
D.
Kristen
Kristen is a feminine given name commonly used in English-speaking countries, often associated with notable figures in entertainment and public life.
-
E.
Kristen
Kristen is the birth name of Kris Jenner, the American television personality and matriarch of the Kardashian–Jenner family.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69b3453a36908190b95a79a297ca083c |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3554a0e7c8190b704d00d07b1857d |
completed | March 13, 2026, 12:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5f62bbee48190bae8fc7b9cc29086 |
completed | March 14, 2026, 11:58 p.m. |
| NEDg | Description generation | batch_69b5f6b132a88190950cde007375965a |
completed | March 15, 2026, midnight |
| NED2 | Entity disambiguation (via description) | batch_69b5f7794d7081909eb494c2119eaee7 |
completed | March 15, 2026, 12:04 a.m. |
Created at: March 12, 2026, 11:30 p.m.