Triple
T9516704
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pope Hilarius |
E229543
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Hilary |
E335389
|
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: Hilary | Statement: [Pope Hilarius, alsoKnownAs, Hilary]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hilary Context triple: [Pope Hilarius, alsoKnownAs, Hilary]
-
A.
Hilary
chosen
Hilary is a given name most notably borne by the influential American philosopher Hilary Putnam.
-
B.
Hillary
Hillary is a surname most prominently associated with New Zealand mountaineer Sir Edmund Hillary and his family, including his son Peter Hillary.
-
C.
Hillary Clinton
Hillary Clinton is an American politician and diplomat who served as U.S. Secretary of State, U.S. senator from New York, First Lady, and the first woman to be a major party’s presidential nominee.
-
D.
Michelle
Michelle is a Fossil Group watch and accessories brand known for its fashion-forward, feminine designs and luxury-inspired styling.
-
E.
Michelle
Michelle is the resourceful and determined protagonist of the psychological thriller film "10 Cloverfield Lane."
- 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_69ca84777560819084cddd999badc1aa |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd987eefec8190b0db1928776bf02b |
completed | April 1, 2026, 10:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d14c183fa08190a28610045306db6d |
completed | April 4, 2026, 5:36 p.m. |
Created at: March 30, 2026, 7:58 p.m.