Triple
T5905921
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tianfu Square |
E131339
|
entity |
| Predicate | hasDesignatedFunction |
P88
|
FINISHED |
| Object | civic space |
—
|
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: civic space | Statement: [Tianfu Square, hasDesignatedFunction, civic space]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDesignatedFunction Context triple: [Tianfu Square, hasDesignatedFunction, civic space]
-
A.
hasPrimaryFunction
chosen
Indicates that one entity serves as the main or principal function or role of another entity.
-
B.
hasPortionDesignatedAs
Indicates that one entity has a specific part or segment that is explicitly identified or designated as another entity.
-
C.
usesFunction
Indicates that one entity employs, invokes, or relies on a particular function to perform an operation or achieve a result.
-
D.
hadFunction
Indicates that an entity previously served or fulfilled a particular role, purpose, or function.
-
E.
hasFictionalFunction
Indicates that an entity serves a role, purpose, or function within a fictional context or narrative.
- 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_69c0085864a88190a569c05ff7d65f29 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c03ee10b308190afe38b904ae7c5f7 |
completed | March 22, 2026, 7:11 p.m. |
| PD | Predicate disambiguation | batch_69c0334fcf6481908e8e74105de9d49b |
completed | March 22, 2026, 6:22 p.m. |
Created at: March 22, 2026, 3:59 p.m.