Triple
T16233025
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | McCreery |
E394036
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | MacCreery |
E394036
|
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: MacCreery | Statement: [McCreery, hasVariant, MacCreery]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MacCreery Context triple: [McCreery, hasVariant, MacCreery]
-
A.
McCreery
chosen
McCreery is a surname of Irish and Scottish origin borne by various notable individuals in fields such as the military, politics, and the arts.
-
B.
Darby McDevitt
Darby McDevitt is a video game writer best known for his work on multiple Assassin's Creed titles, where he helped shape the series' complex narratives and lore.
-
C.
MacLean
MacLean is a Scottish surname most famously associated with bestselling thriller and adventure novelist Alistair MacLean.
-
D.
Michael Ray
Michael Ray is a screenwriter known for his work on the film adaptation of "Snow Flower and the Secret Fan."
-
E.
Tom MacRae
Tom MacRae is a British television writer and playwright best known for his work on Doctor Who and the stage musical Everybody’s Talking About Jamie.
- 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_69d87f204df88190a8f88923decf9835 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e23d2b0cc48190853919135d5a172a |
completed | April 17, 2026, 2:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0007a28ff481908444393f2a6b1fac |
completed | May 10, 2026, 4:20 a.m. |
Created at: April 10, 2026, 5:04 a.m.