Triple
T2854493
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heathfield |
E63167
|
entity |
| Predicate | hasPrimarySettlementType |
P1068
|
FINISHED |
| Object | urban district |
—
|
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: urban district | Statement: [Heathfield, hasPrimarySettlementType, urban district]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrimarySettlementType Context triple: [Heathfield, hasPrimarySettlementType, urban district]
-
A.
hasMainLocationType
Indicates that an entity is associated with a primary or predominant type of location that characterizes where it is mainly situated or operates.
-
B.
hasCityStatusSettlement
Indicates that a settlement possesses official recognition or designation as a city.
-
C.
hasHumanSettlement
Indicates that a location or area contains or is the site of a human settlement, such as a town, village, or city.
-
D.
settlementType
chosen
Indicates the specific kind or category of human settlement an entity represents, such as a city, village, town, or hamlet.
-
E.
typicalSettlementCountry
Indicates the country in which an entity’s financial transactions, obligations, or trades are most commonly settled.
- 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_69ab4c407c408190857d25e027155ce9 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abdf60852c8190b66c8719c63a723e |
completed | March 7, 2026, 8:18 a.m. |
| PD | Predicate disambiguation | batch_69abdd10aef88190b750aae07e7df4dc |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 10:02 p.m.