Triple
T13780320
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sky Studios |
E331114
|
entity |
| Predicate | produced |
P490
|
FINISHED |
| Object | Temple |
E1015940
|
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: Temple | Statement: [Sky Studios, produced, Temple]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Temple Context triple: [Sky Studios, produced, Temple]
-
A.
Temple
Temple is a mid-sized city in central Texas known as a regional medical and transportation hub.
-
B.
Temple
Temple is a surname of English origin borne by various notable individuals across fields such as politics, sports, and the arts.
-
C.
Temple
Temple is a Paris Métro station in central Paris, serving line 3 near the Place de la République.
-
D.
Temple
chosen
"Temple" is a British television drama series produced by Liza Marshall, centered on an underground clinic beneath London where a surgeon treats criminals and desperate patients.
-
E.
Temple
Temple is a historic legal district in central London, renowned for housing the Inns of Court and many barristers’ chambers.
- 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_69d81c583b0081909e408a17db517a21 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de02460a688190a27874f8d35819c7 |
completed | April 14, 2026, 9 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7b079013881908e9f5412e5dfb0b2 |
completed | May 3, 2026, 8:30 p.m. |
Created at: April 9, 2026, 10:11 p.m.