Triple
T6315151
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Denis O'Hare |
E141596
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Milk |
E185021
|
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: Milk | Statement: [Denis O'Hare, notableWork, Milk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Milk Context triple: [Denis O'Hare, notableWork, Milk]
-
A.
Milk
chosen
Milk is a 2008 biographical film about gay rights activist and politician Harvey Milk, directed by Gus Van Sant and starring Sean Penn.
-
B.
Milch
Milch is a German surname most notably borne by Erhard Milch, a high-ranking Luftwaffe officer during World War II.
-
C.
Susu
The Susu are a West African ethnic group primarily found in Guinea, known for their Mande language, Islamic heritage, and significant role in regional trade and culture.
-
D.
Mishti Doi
Mishti Doi is a traditional Bengali dessert of caramelized sweetened yogurt, cherished across India for its rich, creamy taste and distinctive earthen-pot preparation.
-
E.
Water of Milk
Water of Milk is a small river in Dumfries and Galloway in southwest Scotland, known for flowing near the town of Lockerbie.
- 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_69c008d13b8c8190be47d896eb735605 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c064a197488190946c4637b3c829a5 |
completed | March 22, 2026, 9:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c5e46feeec8190bdb39a48c92bacf1 |
completed | March 27, 2026, 1:59 a.m. |
Created at: March 22, 2026, 4:28 p.m.