Triple
T2323228
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abbott, Texas |
E48227
|
entity |
| Predicate | hasSettlementClassification |
P1068
|
FINISHED |
| Object | city in Texas |
—
|
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: city in Texas | Statement: [Abbott, Texas, hasSettlementClassification, city in Texas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSettlementClassification Context triple: [Abbott, Texas, hasSettlementClassification, city in Texas]
-
A.
settlementState
Indicates the state or status of a settlement process or transaction at a given point in time.
-
B.
settlementType
chosen
Indicates the specific kind or category of human settlement an entity represents, such as a city, village, town, or hamlet.
-
C.
associatedWithSettlement
Indicates a relationship where an entity is linked or connected to a particular settlement, such as a town, village, or city.
-
D.
hasSettlementContinuitySince
Indicates that a settlement has existed continuously at a location since a specified point in time.
-
E.
typeOfSettlement
Indicates the specific category or classification of a settlement (e.g., city, town, village) that characterizes what kind of settlement it is.
- 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_69a88aa308a88190b0b86c011fda7fce |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc685f05481909c863b29d1f6bacd |
completed | March 7, 2026, 6:32 a.m. |
| PD | Predicate disambiguation | batch_69abc5909cc48190aab257313542dc49 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:49 p.m.