Triple
T19761491
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Steelers Country |
E474639
|
entity |
| Predicate | hasThemedAreaType |
P6142
|
FINISHED |
| Object | NFL-themed area |
—
|
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: NFL-themed area | Statement: [Steelers Country, hasThemedAreaType, NFL-themed area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasThemedAreaType Context triple: [Steelers Country, hasThemedAreaType, NFL-themed area]
-
A.
containsThemeArea
chosen
Indicates that one entity includes or encompasses a specific thematic area as part of its scope or content.
-
B.
hasThemeType
Indicates that something is associated with or characterized by a particular thematic category or type.
-
C.
hasAreaType
Indicates that an entity is associated with a specific kind or classification of area (e.g., urban, rural, coastal).
-
D.
hasPlayAreaType
Indicates the specific kind or category of play area associated with an entity (e.g., indoor, outdoor, playground type).
-
E.
hasThemingDetail
Indicates that something includes or is associated with a specific thematic element, motif, or stylistic detail.
- 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_69d8e51a43a08190956bc6df13c91a77 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6532004d08190944234d35e74085b |
completed | April 20, 2026, 4:24 p.m. |
| PD | Predicate disambiguation | batch_69e5305016e08190b9561a96baecb0b8 |
completed | April 19, 2026, 7:43 p.m. |
Created at: April 10, 2026, 1:48 p.m.