Triple
T13902421
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Him & Her |
E334258
|
entity |
| Predicate | director |
P255
|
FINISHED |
| Object | Richard Laxton |
E296753
|
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: Richard Laxton | Statement: [Him & Her, director, Richard Laxton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Richard Laxton Context triple: [Him & Her, director, Richard Laxton]
-
A.
Richard Laxton
chosen
Richard Laxton is a British film and television director known for his work on dramas such as the period film "Effie Gray."
-
B.
Richard Lestock
Richard Lestock was an 18th-century British Royal Navy admiral best known for his controversial role in the War of the Austrian Succession and the ensuing court-martial over his conduct in battle.
-
C.
James Laxton
James Laxton is an American cinematographer best known for his acclaimed, visually distinctive work on the Oscar-winning film "Moonlight."
-
D.
William Lambton
William Lambton was a British army officer and surveyor best known for initiating and leading the early phases of the Great Trigonometrical Survey of India in the early 19th century.
-
E.
Richard Suckle
Richard Suckle is an American film producer known for his work on major studio projects, including the DC superhero film "Wonder Woman" (2017).
- 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_69d81c5eaa9c819083b1ff8689179565 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de25d9c7a48190ad8fb0ca676f4f7b |
completed | April 14, 2026, 11:32 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd6d72a17c8190b63f9f441731917d |
completed | May 8, 2026, 4:58 a.m. |
Created at: April 9, 2026, 10:16 p.m.