Triple
T15861279
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Olenna Tyrell |
E384591
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Tyrell
Tyrell is a prominent noble house in the world of "Game of Thrones" and "A Song of Ice and Fire," known for its wealth, influence, and rule over the fertile Reach from its seat at Highgarden.
|
E1180838
|
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: Tyrell | Statement: [Olenna Tyrell, familyName, Tyrell]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tyrell Context triple: [Olenna Tyrell, familyName, Tyrell]
-
A.
Tyrell
Tyrell is a character known for being the adopted child of Rome Howard in the television drama "A Million Little Things."
-
B.
Marto
Marto is a writer best known for contributing to the song "Young, Wild & Free."
-
C.
Marto
Marto is a Portuguese surname notably borne by Francisco Marto, one of the child visionaries of the Marian apparitions at Fátima.
-
D.
Antwan
Antwan is the egotistical, money-obsessed CEO and game publisher who serves as the main antagonist in the action-comedy film "Free Guy."
-
E.
Tye
Tye is the first name of American actor Tye Sheridan, known for roles in films like "Mud," "Ready Player One," and the "X-Men" series.
- 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: Tyrell Triple: [Olenna Tyrell, familyName, Tyrell]
Generated description
Tyrell is a prominent noble house in the world of "Game of Thrones" and "A Song of Ice and Fire," known for its wealth, influence, and rule over the fertile Reach from its seat at Highgarden.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tyrell Target entity description: Tyrell is a prominent noble house in the world of "Game of Thrones" and "A Song of Ice and Fire," known for its wealth, influence, and rule over the fertile Reach from its seat at Highgarden.
-
A.
Tyrell
Tyrell is a character known for being the adopted child of Rome Howard in the television drama "A Million Little Things."
-
B.
Marto
Marto is a writer best known for contributing to the song "Young, Wild & Free."
-
C.
Marto
Marto is a Portuguese surname notably borne by Francisco Marto, one of the child visionaries of the Marian apparitions at Fátima.
-
D.
Antwan
Antwan is the egotistical, money-obsessed CEO and game publisher who serves as the main antagonist in the action-comedy film "Free Guy."
-
E.
Tye
Tye is the first name of American actor Tye Sheridan, known for roles in films like "Mud," "Ready Player One," and the "X-Men" series.
- 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_69d86da422088190aac39e32e6c68429 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1555b952481909246f5ebf53df2a9 |
completed | April 16, 2026, 9:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffa9439db481908be2f6d8a3cfbc85 |
completed | May 9, 2026, 9:38 p.m. |
| NEDg | Description generation | batch_69ffaa07df788190bae67f3d9a800331 |
completed | May 9, 2026, 9:41 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffaaa92a648190a09829ef3197223c |
completed | May 9, 2026, 9:44 p.m. |
Created at: April 10, 2026, 4:50 a.m.