Triple
T198143
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | State Emblem of India |
E4042
|
entity |
| Predicate | visibleLions |
P5465
|
FINISHED |
| Object | three |
—
|
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: three | Statement: [State Emblem of India, visibleLions, three]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: visibleLions Context triple: [State Emblem of India, visibleLions, three]
-
A.
lionArmedAndLangued
Indicates that a lion is depicted with its claws and tongue emphasized, typically by being shown and colored distinctly.
-
B.
containsVisionOf
chosen
Indicates that one entity includes, depicts, or embodies a visual representation or image of another entity.
-
C.
seal
Indicates that an agent closes or fastens something so that it is securely shut and often airtight or watertight.
-
D.
covered
Indicates that one entity lies over or on top of another entity so as to conceal, protect, or obscure it.
-
E.
notableVictim
Indicates that the subject is a person or entity who is notably recognized as a victim of the object (such as an event, crime, or harmful action).
- 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_69a254bca59881909a15e1496f1508c7 |
completed | Feb. 28, 2026, 2:36 a.m. |
| NER | Named-entity recognition | batch_69a25be47ea881909c296b30a0d47a65 |
completed | Feb. 28, 2026, 3:07 a.m. |
| PD | Predicate disambiguation | batch_69a25b47481c8190add47c641c977bb9 |
completed | Feb. 28, 2026, 3:04 a.m. |
Created at: Feb. 28, 2026, 2:44 a.m.