Triple
T35008836
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jinx |
E1009891
|
entity |
| Predicate | countryOfOriginInComics |
P26
|
FINISHED |
| Object | India |
E1124
|
NE 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: India | Statement: [Jinx, countryOfOriginInComics, India]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryOfOriginInComics Context triple: [Jinx, countryOfOriginInComics, India]
-
A.
countryOfOriginFictional
Indicates that a fictional work, character, or element originates from or is associated with a particular country within its narrative or setting.
-
B.
speciesOriginFranchise
Indicates the fictional franchise or series from which a given species originates.
-
C.
countryOfOriginOfFranchise
Indicates the country from which a particular franchise originally comes or was first established.
-
D.
placeOfOriginInFiction
Indicates that a fictional character, object, or entity originates from or is first introduced in a specified fictional location or setting.
-
E.
countryOfOrigin
chosen
Indicates the country from which an entity originally comes or was first produced, created, or established.
- F. None of above.
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_69f76dcb716881909f75e4fd60ab2284 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a019d1407588190b3b9b83fca2e61fe |
completed | May 11, 2026, 9:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a37bd1800e081908bff91c63ec91a78 |
completed | June 21, 2026, 10:29 a.m. |
| PD | Predicate disambiguation | batch_6a019c760e3081909cfe9c0603727e48 |
completed | May 11, 2026, 9:08 a.m. |
Created at: May 3, 2026, 4:01 p.m.