Triple
T5161757
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Lion King (stage musical) |
E116451
|
entity |
| Predicate | subject |
P450
|
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: [The Lion King (stage musical), subject, Scar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Scar Context triple: [The Lion King (stage musical), subject, 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.
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.
-
D.
Scars
"Scars" is a 2004 rock ballad by Papa Roach that became one of the band’s most commercially successful and recognizable songs, noted for its emotional lyrics about pain and healing.
-
E.
Burn
Burn is a young adult fantasy novel by Patrick Ness that blends dragons, Cold War-era tensions, and themes of prejudice and destiny in a small 1950s American town.
- 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_69bd445edb3881909b93b34d260717fc |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd79268ea48190a22d3350babc153c |
completed | March 20, 2026, 4:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bed92eaed88190bfea287da442d376 |
completed | March 21, 2026, 5:45 p.m. |
Created at: March 20, 2026, 1:44 p.m.