Triple
T5161880
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hamilton (musical) |
E116453
|
entity |
| Predicate | notableSong |
P4
|
FINISHED |
| Object | Burn |
E180764
|
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: Burn | Statement: [Hamilton (musical), notableSong, Burn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Burn Context triple: [Hamilton (musical), notableSong, Burn]
-
A.
Burn
Burn is the first name of Burn Gorman, a British-American actor known for roles in productions such as "Torchwood," "Game of Thrones," and "Pacific Rim."
-
B.
Burn
chosen
"Burn" is a hit pop and EDM-influenced song co-written and produced by Ryan Tedder, best known for being performed by British singer Ellie Goulding.
-
C.
Burn
Burn is the abbreviated name of the former Major League Soccer team Dallas Burn, now known as FC Dallas.
-
D.
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.
-
E.
Burnt
Burnt is a 2015 drama-comedy film about a talented but troubled chef seeking redemption in the high-pressure world of haute cuisine.
- 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.