Triple
T3108080
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vernon Springs, Iowa |
E64881
|
entity |
| Predicate | hasFeatureCode |
P45983
|
FINISHED |
| Object | unincorporated place |
—
|
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: unincorporated place | Statement: [Vernon Springs, Iowa, hasFeatureCode, unincorporated place]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFeatureCode Context triple: [Vernon Springs, Iowa, hasFeatureCode, unincorporated place]
-
A.
hasFeature
Indicates that an entity possesses, exhibits, or includes a particular characteristic, attribute, or component.
-
B.
hasFeatureID
Indicates that an entity is associated with a specific feature identified by a unique ID.
-
C.
supportsFeature
Indicates that one entity provides, enables, or is compatible with a particular feature or capability of another.
-
D.
hasFAACode
Indicates that an entity is associated with a specific FAAC (Federal Aviation Administration Code) identifier.
-
E.
hasMIC
Indicates that an entity has a specified Minimum Inhibitory Concentration (MIC) value in relation to an antimicrobial agent.
- F. None of above. chosen
Provenance (4 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_69ad857eeaf48190b34ebfdaa7a264cf |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada29eacc88190a19c5ca8e53e3dca |
completed | March 8, 2026, 4:23 p.m. |
| PD | Predicate disambiguation | batch_69ad9df25d4c81908ff0f6cff55d0563 |
completed | March 8, 2026, 4:04 p.m. |
| PDg | Predicate description generation | batch_69ada0f6fef48190b13898be383a246b |
completed | March 8, 2026, 4:16 p.m. |
Created at: March 8, 2026, 3:04 p.m.