Triple
T19963529
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chandraghanta |
E479873
|
entity |
| Predicate | foreheadMark |
P99152
|
FINISHED |
| Object | crescent moon |
—
|
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: crescent moon | Statement: [Chandraghanta, foreheadMark, crescent moon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: foreheadMark Context triple: [Chandraghanta, foreheadMark, crescent moon]
-
A.
facialMarkings
Indicates that one entity has distinctive marks, patterns, or features on its face in relation to another entity or context.
-
B.
eggMarkings
Indicates that one entity bears or displays specific markings or patterns on its eggs in relation to another entity or context.
-
C.
armorMarkings
Indicates that one entity bears specific markings, patterns, or insignia on its armor in relation to another entity or context.
-
D.
leafMarkings
Indicates the presence, pattern, or characteristics of markings found on the surface of a leaf.
-
E.
markingFeature
chosen
Indicates a feature that serves as a distinguishing mark or identifier associated with an entity.
- 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_69d8e523c19881909f9197037200dde6 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65af619108190825cbcfb6b8e1fa5 |
completed | April 20, 2026, 4:57 p.m. |
| PD | Predicate disambiguation | batch_69e537f7e4848190b431a69ec3f1b609 |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 10, 2026, 1:54 p.m.