Triple
T14336563
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Disney characters |
E355479
|
entity |
| Predicate | notableCharacter |
P1481
|
FINISHED |
| Object | Scar |
E173069
|
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: Scar | Statement: [Disney characters, notableCharacter, Scar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Scar Context triple: [Disney characters, notableCharacter, Scar]
-
A.
Scar
chosen
Scar is the cunning and power-hungry lion antagonist in Disney's animated film "The Lion King," known for plotting to overthrow his brother Mufasa and nephew Simba.
-
B.
Scar
Scar is the ruthless Comanche chief who serves as the primary adversary in the classic Western film "The Searchers."
-
C.
Scar
Scar is a vengeful Ishvalan warrior and key antagonist-turned-antihero in Fullmetal Alchemist, known for using his alchemically enhanced arm to destroy his enemies.
-
D.
Scar
Scar is a visual and musical segment from Beyoncé’s film and album "Black Is King," thematically exploring legacy, identity, and the scars of generational trauma.
-
E.
Scars
"Scars" is a soulful, emotionally charged song by British singer-songwriter James Bay that reflects on vulnerability, healing, and the lingering impact of past relationships.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d8278fa2108190bc0d0e7939c1eb03 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de8c2241e48190a0c626b3d741966a |
completed | April 14, 2026, 6:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd46986758819088750150ad47bae1 |
completed | May 8, 2026, 2:12 a.m. |
Created at: April 10, 2026, 1:14 a.m.