Triple
T28066085
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Imam Hossein Square |
E709253
|
entity |
| Predicate | hasNearbyEntityType |
P193931
|
FINISHED |
| Object | commercial buildings |
—
|
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: commercial buildings | Statement: [Imam Hossein Square, hasNearbyEntityType, commercial buildings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyEntityType Context triple: [Imam Hossein Square, hasNearbyEntityType, commercial buildings]
-
A.
hasNotableNearbyEntity
Indicates that one entity has another significant or noteworthy entity located in its close physical or contextual proximity.
-
B.
hasNearbyEventType
Indicates that an event of a specified type occurs in close spatial or contextual proximity to a given reference entity or location.
-
C.
hasNearbySiteType
Indicates that one entity has another entity of a specified site type located in its close physical vicinity.
-
D.
hasNearbyFunction
Indicates that one entity has another entity located close by that serves a related or supportive function.
-
E.
hasNearbyInfrastructureType
Indicates that an entity is located close to infrastructure of a specified type.
- 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_69ef9b6eb6d88190a3fea236eb0f7bed |
completed | April 27, 2026, 5:22 p.m. |
| NER | Named-entity recognition | batch_69fd5bf69acc819092a01e4259785dc3 |
completed | May 8, 2026, 3:43 a.m. |
| PD | Predicate disambiguation | batch_69fd59b3f4ac8190a7f9dd3142da6e09 |
completed | May 8, 2026, 3:34 a.m. |
| PDg | Predicate description generation | batch_69fd5bf49288819098a12202411cba4f |
completed | May 8, 2026, 3:43 a.m. |
Created at: April 27, 2026, 8:43 p.m.