Triple

T26527002
Position Surface form Disambiguated ID Type / Status
Subject Thomas Turgoose E670715 entity
Predicate appearedIn P795 FINISHED
Object The Gallows Pole
The Gallows Pole is a British period crime drama television series, directed by Shane Meadows and based on Benjamin Myers’ novel about 18th-century coiners in Yorkshire.
E1731852 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: The Gallows Pole | Statement: [Thomas Turgoose, appearedIn, The Gallows Pole]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: The Gallows Pole
Triple: [Thomas Turgoose, appearedIn, The Gallows Pole]
Generated description
The Gallows Pole is a British period crime drama television series, directed by Shane Meadows and based on Benjamin Myers’ novel about 18th-century coiners in Yorkshire.

Provenance (5 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_69eeb31ea1e08190b9ff43cf9bc25bf8 completed April 27, 2026, 12:51 a.m.
NER Named-entity recognition batch_69f613f41ccc8190b8bcc027ba1d0b93 completed May 2, 2026, 3:10 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11c811cce88190aa313c108f47967a completed May 23, 2026, 3:30 p.m.
NEDg Description generation batch_6a11c990b5b0819089db74aa73b886a0 completed May 23, 2026, 3:36 p.m.
NED2 Entity disambiguation (via description) batch_6a11ca6f162c8190a8c7fbc1e188ea90 completed May 23, 2026, 3:40 p.m.
Created at: April 27, 2026, 1:32 a.m.