Triple
T11472079
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arvad |
E271931
|
entity |
| Predicate | presentDaySettlementType |
P26700
|
FINISHED |
| Object | town |
—
|
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: town | Statement: [Arvad, presentDaySettlementType, town]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: presentDaySettlementType Context triple: [Arvad, presentDaySettlementType, town]
-
A.
settlementType
Indicates the specific kind or category of human settlement an entity represents, such as a city, village, town, or hamlet.
-
B.
typeOfSettlement
chosen
Indicates the specific category or classification of a settlement (e.g., city, town, village) that characterizes what kind of settlement it is.
-
C.
previousSettlementType
Indicates the type or classification of a settlement that existed at a location before the current or present settlement type.
-
D.
settlementMode
Indicates the method or process by which a financial or transactional obligation is settled or completed between parties.
-
E.
settlementPattern
Indicates how human dwellings or communities are spatially arranged and distributed across a geographic area.
- 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_69d6aae0c8d881908a5a360c0be3242e |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8294b3f388190a587c358313f7260 |
completed | April 9, 2026, 10:33 p.m. |
| PD | Predicate disambiguation | batch_69d8086ecd6c81908f424864857762d6 |
completed | April 9, 2026, 8:13 p.m. |
Created at: April 8, 2026, 9:35 p.m.