Triple
T33718358
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Biddu |
E863937
|
entity |
| Predicate | hasLandClassification |
P198794
|
FINISHED |
| Object | Area B |
—
|
NE NERFINISHED |
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: Area B | Statement: [Biddu, hasLandClassification, Area B]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLandClassification Context triple: [Biddu, hasLandClassification, Area B]
-
A.
hasLandStatus
Indicates that an entity possesses a particular legal or administrative status regarding land (such as ownership, tenure, protection, or use designation).
-
B.
hasLandUseCharacter
Indicates that one entity possesses or is associated with a particular type or pattern of land use.
-
C.
isInLandAreaType
Indicates that one entity is located within, or belongs to, a specified type of land area (such as urban, rural, coastal, or agricultural).
-
D.
hasLandUseSystem
Indicates that an entity is associated with or characterized by a particular system or pattern of land use.
-
E.
hasLikelyLandUse
Indicates that an area or parcel is associated with a predicted or most probable type of land use (e.g., residential, commercial, agricultural).
- 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_69f34989871c81908682e22a2fe4b829 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69ff069ec1348190815375c5c9e38404 |
completed | May 9, 2026, 10:04 a.m. |
| PD | Predicate disambiguation | batch_69ff05ba57f88190a45d20f18044e0fb |
completed | May 9, 2026, 10 a.m. |
| PDg | Predicate description generation | batch_69ff069ddf948190bdfe438953249dd0 |
completed | May 9, 2026, 10:04 a.m. |
Created at: May 1, 2026, 1:44 a.m.