Triple
T18867444
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | He Who Is in the Place of Embalming |
E461475
|
entity |
| Predicate | associatedWithLocationType |
P69710
|
FINISHED |
| Object | embalming workshop |
—
|
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: embalming workshop | Statement: [He Who Is in the Place of Embalming, associatedWithLocationType, embalming workshop]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithLocationType Context triple: [He Who Is in the Place of Embalming, associatedWithLocationType, embalming workshop]
-
A.
associatedWithLocality
Indicates a relationship where something has a connection or relevance to a specific geographic place or locality.
-
B.
associatedWithTeamLocation
Indicates that an entity has a relationship or connection to the geographic location of a specific team.
-
C.
positionAssociatedWith
Indicates a relationship where a specific role, job, or position is linked or connected to a particular entity, context, or resource.
-
D.
hasLocationRole
chosen
Indicates that an entity holds or plays a specific role in relation to a particular location (e.g., origin, destination, storage site, or operational area).
-
E.
associatedWithAirportType
Indicates that an entity has a connection or linkage to a specific category or type of airport.
- F. None of above.
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_69d8dcfb7b9c8190854e7b171b98ea2e |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c2a6d1d081909b6dab2a5166a317 |
completed | April 20, 2026, 6:07 a.m. |
| PD | Predicate disambiguation | batch_69e48d2166b88190add38de96cedc65c |
completed | April 19, 2026, 8:06 a.m. |
Created at: April 10, 2026, 11:57 a.m.