Triple
T16327207
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nunhead Cemetery |
E396451
|
entity |
| Predicate | hasChapelStatus |
P122725
|
FINISHED |
| Object | ruined Anglican chapel |
—
|
LITERAL 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: ruined Anglican chapel | Statement: [Nunhead Cemetery, hasChapelStatus, ruined Anglican chapel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasChapelStatus Context triple: [Nunhead Cemetery, hasChapelStatus, ruined Anglican chapel]
-
A.
hasChapelRequirement
Indicates that an entity is subject to a requirement to attend or participate in chapel or religious services.
-
B.
hasChapelUse
Indicates that something is used, designated, or functions as a chapel or for chapel-related purposes.
-
C.
hasChapelLocation
Indicates that one entity serves as the physical location or site where a chapel associated with another entity is situated.
-
D.
hasChapelHonoring
Indicates that one entity contains or includes a chapel dedicated to honoring another entity.
-
E.
hasChapelStyle
Indicates that a chapel possesses or is characterized by a particular architectural or stylistic design.
- F. None of above. chosen
Provenance (4 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_69d87f255b788190a400eba031dd85d8 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e296bab8b48190b373b4efbd6f0d8c |
completed | April 17, 2026, 8:23 p.m. |
| PD | Predicate disambiguation | batch_69e219fc72c881909d452274e7af8238 |
completed | April 17, 2026, 11:31 a.m. |
| PDg | Predicate description generation | batch_69e21e56e0348190a3d9475360231a70 |
completed | April 17, 2026, 11:49 a.m. |
Created at: April 10, 2026, 5:07 a.m.