Triple
T22857536
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Geoff Pierson |
E566823
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Geoff |
—
|
NE NERFINISHED |
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: Geoff | Statement: [Geoff Pierson, givenName, Geoff]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Geoff Context triple: [Geoff Pierson, givenName, Geoff]
-
A.
Geoff
chosen
Geoff is a masculine given name, often used as a shortened form of Geoffrey.
-
B.
Geoff Dartt
Geoff Dartt is an American college football coach best known for leading the powerhouse Mount Union Purple Raiders program.
-
C.
Geoff Howard
Geoff Howard is a name shared by multiple individuals, including public figures such as politicians and professionals in various fields.
-
D.
Graeme
Graeme is a masculine given name of Scottish origin, commonly used in English-speaking countries.
-
E.
Gareth
Gareth is a masculine given name of Welsh origin, commonly used in English-speaking countries.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e24589083081908d5694c4fdc80086 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17ebe3f9c8190a864f4e84dc7795d |
completed | April 29, 2026, 3:45 a.m. |
Created at: April 17, 2026, 3:37 p.m.