Triple
T6412240
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ernie Banks |
E127733
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Ernest |
E49898
|
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: Ernest | Statement: [Ernie Banks, givenName, Ernest]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ernest Context triple: [Ernie Banks, givenName, Ernest]
-
A.
Ernest
chosen
Ernest is a masculine given name of Germanic origin meaning "serious" or "resolute," borne by numerous notable figures across history and culture.
-
B.
Maurice
Maurice is a 1987 British romantic drama film, based on E.M. Forster’s novel, that explores same-sex love and class in early 20th-century England.
-
C.
Maurice
Maurice is a masculine given name of Latin origin, commonly used in English and French-speaking countries.
-
D.
Homer Bigart
Homer Bigart was a Pulitzer Prize–winning American war correspondent renowned for his frontline reporting in conflicts such as World War II, the Korean War, and the Vietnam War.
-
E.
Earl
An Earl is a noble rank in the British and some European peerage systems, historically positioned below a marquess and above a viscount.
- 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_69c0083723d88190b1e37b19df162c08 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c068d228208190ba05eeb7707482fe |
completed | March 22, 2026, 10:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c640c48e688190981a19ce5eb2af44 |
completed | March 27, 2026, 8:33 a.m. |
Created at: March 22, 2026, 4:42 p.m.