Triple
T18994406
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tappitt |
E464770
|
entity |
| Predicate | hasNameForm |
P19207
|
FINISHED |
| Object | Tappitt |
—
|
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: Tappitt | Statement: [Tappitt, hasNameForm, Tappitt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tappitt Context triple: [Tappitt, hasNameForm, Tappitt]
-
A.
Tappitt
chosen
Tappitt is a surname associated with the individual referred to as Mr. Tappitt.
-
B.
Tamu
Tamu is a town in northwestern Myanmar’s Sagaing Region, situated near the India–Myanmar border and serving as an important cross-border trade and transit point.
-
C.
Baylor
Baylor is a surname most notably associated with American baseball player and manager Don Baylor.
-
D.
Tarleton
Tarleton is a village in Lancashire, England, situated in a rural area of the West Lancashire Coastal Plain near the River Douglas.
-
E.
Baylor University
Baylor University is a private Christian research university in Waco, Texas, known for its strong academic programs and prominent athletics in the Big 12 Conference.
- 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_69d8dd01a56c81909694a128c66b21d7 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d680dd2881908a72e732c6b25477 |
completed | April 20, 2026, 7:32 a.m. |
Created at: April 10, 2026, 12:01 p.m.