Triple
T82620
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chi-Town |
E1659
|
entity |
| Predicate | refersToFeature |
P37
|
FINISHED |
| Object | urban identity of Chicago |
—
|
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 identity of Chicago | Statement: [Chi-Town, refersToFeature, urban identity of Chicago]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: refersToFeature Context triple: [Chi-Town, refersToFeature, urban identity of Chicago]
-
A.
canRefer
Indicates that one entity has the ability or permission to mention, point to, or direct attention to another entity.
-
B.
relatedTo
chosen
Indicates a general, non-specific relationship or association exists between two entities.
-
C.
appliesTo
Indicates that something is relevant, valid, or has effect in relation to a particular entity, case, or context.
-
D.
connectsTo
Indicates a relationship where one entity is linked or joined to another, allowing interaction, communication, or transfer between them.
-
E.
supportsFeature
Indicates that one entity provides, enables, or is compatible with a particular feature or capability of another.
- 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_69a24c8150408190910a693eb51c1f71 |
completed | Feb. 28, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69a25053ca208190a371b0d38000c2b9 |
completed | Feb. 28, 2026, 2:17 a.m. |
| PD | Predicate disambiguation | batch_69a24eb2998c819082681da74601d446 |
completed | Feb. 28, 2026, 2:10 a.m. |
Created at: Feb. 28, 2026, 2:06 a.m.