Triple
T30704684
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stanton, Iowa |
E781718
|
entity |
| Predicate | hasWaterTowerShape |
P4141
|
FINISHED |
| Object | coffee pot |
—
|
LITERAL 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: coffee pot | Statement: [Stanton, Iowa, hasWaterTowerShape, coffee pot]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWaterTowerShape Context triple: [Stanton, Iowa, hasWaterTowerShape, coffee pot]
-
A.
waterTowerBuiltIn
Indicates that a water tower was constructed in a specific location or during a specific time period.
-
B.
waterTowerFunction
Indicates that an entity serves the role or function of a water tower, typically storing and supplying water within a system or area.
-
C.
hasDomeOrTower
Indicates that one entity possesses or features a dome or a tower as part of its structure.
-
D.
towerShape
chosen
Indicates that one entity has the physical form or outline of a tower in relation to another entity.
-
E.
hasIconicRoofShape
Indicates that an entity possesses a roof with a distinctive, widely recognized, or characteristic shape.
- F. None of above.
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_69f224abfcf081909492e64d3cc35262 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f72921cf2c8190909bb53f78bcc890 |
completed | May 3, 2026, 10:53 a.m. |
| PD | Predicate disambiguation | batch_69f7283d8cec8190b524c144948bc4ec |
completed | May 3, 2026, 10:49 a.m. |
Created at: April 29, 2026, 8:35 p.m.