Triple

T36414280
Position Surface form Disambiguated ID Type / Status
Subject Hertford Union Canal E896961 entity
Predicate hasLock P2431 FINISHED
Object Hertford Union Bottom Lock
Hertford Union Bottom Lock is one of the canal locks on the Hertford Union Canal in East London, used to raise and lower boats between different water levels.
E2184402 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: Hertford Union Bottom Lock | Statement: [Hertford Union Canal, hasLock, Hertford Union Bottom Lock]
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: Hertford Union Bottom Lock
Triple: [Hertford Union Canal, hasLock, Hertford Union Bottom Lock]
Generated description
Hertford Union Bottom Lock is one of the canal locks on the Hertford Union Canal in East London, used to raise and lower boats between different water levels.

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_69f76e54ce408190849acc3f7758937c completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7bd3275b88190a84791b747f3f3f6 completed May 3, 2026, 9:25 p.m.
NED1 Entity disambiguation (via context triple) batch_6a39c40801448190a9f0bf67d621ddc1 completed June 22, 2026, 11:23 p.m.
NEDg Description generation batch_6a39c6208b8081908c69eed0cc8c0a13 completed June 22, 2026, 11:32 p.m.
NED2 Entity disambiguation (via description) batch_6a39c91128dc8190add6788dcc8a9f54 completed June 22, 2026, 11:45 p.m.
Created at: May 3, 2026, 4:10 p.m.