Triple
T2494874
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emblem of Pakistan |
E52131
|
entity |
| Predicate | featuresStar |
P39789
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Emblem of Pakistan, featuresStar, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresStar Context triple: [Emblem of Pakistan, featuresStar, true]
-
A.
featuresText
Indicates that an entity includes or presents a specific piece of text as one of its characteristics or contents.
-
B.
featuresHero
Indicates that something (such as a work, product, or story) prominently includes or centers around a particular hero as a main character or focus.
-
C.
featuresCross
Indicates that one feature or element intersects or passes across another in space or structure.
-
D.
featuresReimaginedVersionOf
Indicates that something includes or presents a newly interpreted or updated version of another existing work or element.
-
E.
featuresSegment
Indicates that one entity includes or highlights a particular segment or portion of another entity as a notable part of it.
- F. None of above. chosen
Provenance (4 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_69ab4955111c8190835bf619adec21ff |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd19541048190b9e39db119c20fe8 |
completed | March 7, 2026, 7:19 a.m. |
| PD | Predicate disambiguation | batch_69abd0b980b481908d4932bcea4a6167 |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd1318f7881908a8fc42943df4879 |
completed | March 7, 2026, 7:18 a.m. |
Created at: March 6, 2026, 9:45 p.m.