Triple
T7438722
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deltona |
E171688
|
entity |
| Predicate | hasNeighboringCity |
P3883
|
FINISHED |
| Object | DeBary |
E515781
|
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: DeBary | Statement: [Deltona, hasNeighboringCity, DeBary]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DeBary Context triple: [Deltona, hasNeighboringCity, DeBary]
-
A.
DeBary
chosen
DeBary is a small city in central Florida known as a residential community along the St. Johns River in Volusia County.
-
B.
Diadema
Diadema is an industrial and densely populated municipality in the Greater São Paulo metropolitan area of southeastern Brazil.
-
C.
Heinsius
Heinsius is a Dutch surname most notably associated with Anthonie Heinsius, a prominent statesman of the Dutch Republic in the late 17th and early 18th centuries.
-
D.
Myrtle
Myrtle is a central romantic character in Richard Steele’s early 18th-century sentimental comedy "The Conscious Lovers," embodying the play’s themes of virtue, sensibility, and refined love.
-
E.
Myrtle
Myrtle is a fictional character appearing in P. G. Wodehouse’s comic novel "Service with a Smile."
- 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_69c68a64228c8190affaec2a8127ce7b |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f34aa3388190ac300cf934042d78 |
completed | March 27, 2026, 9:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8278cd9cc8190b88767c1432b3007 |
completed | March 28, 2026, 7:10 p.m. |
Created at: March 27, 2026, 3:13 p.m.