Triple
T14780631
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gilly |
E347379
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object | Hannah Murray |
E823956
|
NE FINISHED |
How this triple was built (2 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: Hannah Murray | Statement: [Gilly, portrayedBy, Hannah Murray]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hannah Murray Context triple: [Gilly, portrayedBy, Hannah Murray]
-
A.
Hannah Murray
chosen
Hannah Murray is an English actress best known for her roles as Cassie Ainsworth in the TV series "Skins" and Gilly in "Game of Thrones."
-
B.
Maggie Mills
Maggie Mills is the female lead in the comedy film "Hall Pass," portrayed as a suburban wife whose marriage is tested when her husband is granted a week-long break from marital fidelity.
-
C.
Haley Hudson
Haley Hudson is an American actress best known for her roles in horror and supernatural films and television series.
-
D.
Jessica Henwick
Jessica Henwick is a British actress known for her roles in genre franchises such as "Game of Thrones," "Star Wars: The Force Awakens," and various action and science fiction films and series.
-
E.
Lili Reinhart
Lili Reinhart is an American actress best known for playing Betty Cooper on the television series "Riverdale."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d822e9b9e08190bedcc31a163fda82 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deca9c7cac8190ba900df95e42e318 |
completed | April 14, 2026, 11:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe0d00d46c8190b6289a9b8511a8fb |
completed | May 8, 2026, 4:19 p.m. |
Created at: April 10, 2026, 1:31 a.m.