Triple
T7445444
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Showplace of the Nation |
E171864
|
entity |
| Predicate | relatedToIndustry |
P47404
|
FINISHED |
| Object | entertainment industry |
—
|
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: entertainment industry | Statement: [Showplace of the Nation, relatedToIndustry, entertainment industry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatedToIndustry Context triple: [Showplace of the Nation, relatedToIndustry, entertainment industry]
-
A.
relationToIndustry
chosen
Indicates how an entity is connected or relevant to a particular industry, such as through involvement, impact, or association.
-
B.
containsIndustry
Indicates that one entity includes or encompasses a particular industry within its scope, structure, or operations.
-
C.
isPartOfIndustry
Indicates that one entity belongs to, operates within, or is categorized under a particular industry sector.
-
D.
relatedTo
Indicates a general, non-specific relationship or association exists between two entities.
-
E.
relatedProfession
Indicates that two entities have professions that are connected or associated in some meaningful way, such as being in the same field, industry, or professional domain.
- 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_69c68a65402881908f7869368eb746fb |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f37054388190a6cb4c0db2ca6014 |
completed | March 27, 2026, 9:15 p.m. |
| PD | Predicate disambiguation | batch_69c6f039f7248190bb4183f97b605763 |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:14 p.m.