Triple
T14671917
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John McCloskey |
E344533
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | McCloskey |
E344533
|
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: McCloskey | Statement: [John McCloskey, familyName, McCloskey]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: McCloskey Context triple: [John McCloskey, familyName, McCloskey]
-
A.
McCloskey
chosen
McCloskey is a surname most notably associated with John Cardinal McCloskey, the first American cardinal in the Roman Catholic Church.
-
B.
Cowles
Cowles is a surname most notably associated with Henry Chandler Cowles, an influential American botanist and pioneer of ecological succession studies.
-
C.
Leacock-Pennebaker
Leacock-Pennebaker was a pioneering American documentary film production company known for its influential cinéma vérité works in the 1960s.
-
D.
McClurg
McClurg is the namesake of the historic McClurg Building, a notable structure recognized for its architectural and cultural significance.
-
E.
Sossick
Sossick is a Nigerian music producer known for crafting influential hip-hop and Afrobeats tracks for prominent artists.
- 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_69d822e283fc8190a0e4c235cf880052 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb55064cc8190b9669d0b2da61825 |
completed | April 14, 2026, 9:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fde17a39b88190b144b6cfcc61a4b8 |
completed | May 8, 2026, 1:13 p.m. |
Created at: April 10, 2026, 1:27 a.m.