Triple
T3664252
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Doomsday |
E77721
|
entity |
| Predicate | musicBy |
P1952
|
FINISHED |
| Object | Murray Gold |
E79471
|
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: Murray Gold | Statement: [Doomsday, musicBy, Murray Gold]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Murray Gold Context triple: [Doomsday, musicBy, Murray Gold]
-
A.
Murray Gold
chosen
Murray Gold is a British composer best known for his dynamic and emotive scores for the revived Doctor Who television series and its spin-offs.
-
B.
Harry Gregson-Williams
Harry Gregson-Williams is a British composer best known for his film and video game scores, including work on the "Shrek" series, "The Chronicles of Narnia," and the "Metal Gear Solid" franchise.
-
C.
Ernest Gold
Ernest Gold was an Austrian-born American composer best known for his acclaimed film scores, including the Oscar-winning music for "Exodus."
-
D.
Ron Goodwin
Ron Goodwin was a British composer and conductor best known for his rousing film scores for war and adventure movies in the mid-20th century.
-
E.
Rupert Gregson-Williams
Rupert Gregson-Williams is a British film and television composer known for scoring major Hollywood productions such as "Wonder Woman," "Aquaman," and "The Crown."
- 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_69ad85dfc4dc8190a441864202ab2a7a |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc3fe5eb08190ab15044acf9ac8a9 |
completed | March 8, 2026, 6:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4c39bb9b48190ba34226ccfccd59e |
completed | March 14, 2026, 2:10 a.m. |
Created at: March 8, 2026, 3:25 p.m.