Triple
T17776869
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Whitehouse, Texas |
E443792
|
entity |
| Predicate | hasHighSchoolColors |
P19185
|
FINISHED |
| Object | maroon and white |
—
|
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: maroon and white | Statement: [Whitehouse, Texas, hasHighSchoolColors, maroon and white]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHighSchoolColors Context triple: [Whitehouse, Texas, hasHighSchoolColors, maroon and white]
-
A.
hasSchoolColours
chosen
Indicates that an entity is associated with one or more official colours that represent it, typically in formal or symbolic contexts.
-
B.
hasHomeUniformTrimColor
Indicates that an entity’s home uniform features a specified trim or accent color.
-
C.
hasJerseyColor
Indicates that an entity’s jersey possesses or is characterized by a specific color.
-
D.
hasClubColor
Indicates that a club or team is associated with a specific color or set of colors used to represent it.
-
E.
hasHomeJerseyColor
Indicates that an entity’s home jersey is characterized by a specified color.
- 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_69d8b9ef17708190bdf7e2adbf14ddc2 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4871d43a481908aacde69bd8091b0 |
completed | April 19, 2026, 7:41 a.m. |
| PD | Predicate disambiguation | batch_69e3d8d8e538819084f1584426b41d5e |
completed | April 18, 2026, 7:17 p.m. |
Created at: April 10, 2026, 10:12 a.m.