Triple
T9820428
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mary-Louise Parker |
E238515
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Mary-Louise
Mary-Louise is a feminine given name most notably associated with American actress Mary-Louise Parker.
|
E825553
|
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: Mary-Louise | Statement: [Mary-Louise Parker, givenName, Mary-Louise]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mary-Louise Context triple: [Mary-Louise Parker, givenName, Mary-Louise]
-
A.
Mary-Lou
Mary-Lou is a timid, kind-hearted schoolgirl who appears as one of the students in Enid Blyton’s Malory Towers series.
-
B.
Maryanne
Maryanne is a feminine given name, often used in English-speaking countries as a variant of Mary Ann or Marianne.
-
C.
Mary Ruth
Mary Ruth is a fictional character featured in the American television sitcom "The Debbie Reynolds Show."
-
D.
Mary Louise
Mary Louise is the given first name of Irish politician Mary Lou McDonald, leader of the Sinn Féin party.
-
E.
Mary Lou
Mary Lou is a technology innovator and entrepreneur best known for her pioneering work in display and imaging technologies, including co-founding One Laptop per Child and founding Openwater.
- 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: Mary-Louise Triple: [Mary-Louise Parker, givenName, Mary-Louise]
Generated description
Mary-Louise is a feminine given name most notably associated with American actress Mary-Louise Parker.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mary-Louise Target entity description: Mary-Louise is a feminine given name most notably associated with American actress Mary-Louise Parker.
-
A.
Mary-Lou
Mary-Lou is a timid, kind-hearted schoolgirl who appears as one of the students in Enid Blyton’s Malory Towers series.
-
B.
Maryanne
Maryanne is a feminine given name, often used in English-speaking countries as a variant of Mary Ann or Marianne.
-
C.
Mary Ruth
Mary Ruth is a fictional character featured in the American television sitcom "The Debbie Reynolds Show."
-
D.
Mary Louise
Mary Louise is the given first name of Irish politician Mary Lou McDonald, leader of the Sinn Féin party.
-
E.
Mary Lou
Mary Lou is a technology innovator and entrepreneur best known for her pioneering work in display and imaging technologies, including co-founding One Laptop per Child and founding Openwater.
- 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_69ca84dfde1481909f47c286d715f892 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb313134081908eb0ba3a22b22e2b |
completed | April 2, 2026, 12:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1d5b599f88190a8f54771c4a75e58 |
completed | April 5, 2026, 3:23 a.m. |
| NEDg | Description generation | batch_69d1d988d8588190b5a8ae071b4fcd40 |
completed | April 5, 2026, 3:39 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d1d9d98b5c8190825a06d57f59d1d3 |
completed | April 5, 2026, 3:41 a.m. |
Created at: March 30, 2026, 8:31 p.m.