Triple
T16866472
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lawrence Talbot |
E410051
|
entity |
| Predicate | setting |
P1957
|
FINISHED |
| Object | Blackmoor |
E410052
|
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: Blackmoor | Statement: [Lawrence Talbot, setting, Blackmoor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Blackmoor Context triple: [Lawrence Talbot, setting, Blackmoor]
-
A.
Blackmoor
chosen
Blackmoor is a fictional, fog-shrouded Victorian English village known as the primary horror setting of the 2010 werewolf film "The Wolfman."
-
B.
Blackmoor
Blackmoor is a small rural village in the East Hampshire district of Hampshire, England, known for its countryside setting and traditional English character.
-
C.
Seal Point
Seal Point is a coastal headland or promontory located near Hope Bay on the Antarctic Peninsula.
-
D.
Blackmoorfoot
Blackmoorfoot is a small rural settlement in the Colne Valley area of West Yorkshire, England, known for its nearby reservoir and moorland surroundings.
-
E.
Calico
Calico is a research and development company founded by Google that focuses on understanding aging and developing technologies to extend human lifespan.
- 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_69d88395e6c88190b22730f335107c14 |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b5088f208190abfe937633ebe3fe |
completed | April 18, 2026, 4:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00c2a929b081909d3a5a680ae93a78 |
completed | May 10, 2026, 5:38 p.m. |
Created at: April 10, 2026, 5:24 a.m.