Triple
T1587374
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New Mexico |
E34095
|
entity |
| Predicate | hasOfficialStateFlagColors |
P19067
|
FINISHED |
| Object | red and yellow |
—
|
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: red and yellow | Statement: [New Mexico, hasOfficialStateFlagColors, red and yellow]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOfficialStateFlagColors Context triple: [New Mexico, hasOfficialStateFlagColors, red and yellow]
-
A.
nationalFlagColor
Indicates that a specific color appears on the national flag of a given country.
-
B.
nationalFlag
Indicates that one entity is the official national flag representing the other entity (a country or nation).
-
C.
subnationalFlagOf
Indicates that one flag represents or is officially used by a subnational entity (such as a state, province, or region) within a larger sovereign country.
-
D.
hasNationalSymbol
Indicates that an entity possesses or is associated with an officially recognized national symbol of a country or nation.
-
E.
stateColours
chosen
Indicates that specific colours are officially associated with or designated for a particular state.
- 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_69a885fceb2c8190b47e0f7c0aefbff0 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a93aedd45c819085843ac843d640e8 |
completed | March 5, 2026, 8:12 a.m. |
| PD | Predicate disambiguation | batch_69a907bdc19081908c84c5c0aa09e282 |
completed | March 5, 2026, 4:34 a.m. |
Created at: March 4, 2026, 7:27 p.m.