Triple
T6441207
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maagdenhuis |
E138227
|
entity |
| Predicate | hasBoardOffices |
P70646
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Maagdenhuis, hasBoardOffices, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBoardOffices Context triple: [Maagdenhuis, hasBoardOffices, yes]
-
A.
hasOffice
Indicates that an entity possesses or maintains an office at a particular location or within a specific organization.
-
B.
servesAsOfficeOf
Indicates that one entity functions as the official office, headquarters, or administrative base for another entity.
-
C.
numberOfOffices
Indicates the total count of offices associated with a given entity.
-
D.
hasAssociatedOffice
Indicates that an entity is linked to or connected with a particular office in an official or functional capacity.
-
E.
memberHoldsOffice
Indicates that a member occupies or serves in a specific official position or office within an organization or governing body.
- 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_69c008aa61ac8190bc96715ed79fe2d8 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c06968c6a88190a623da9bd3152a66 |
completed | March 22, 2026, 10:12 p.m. |
| PD | Predicate disambiguation | batch_69c060f96980819091bab9335922a457 |
completed | March 22, 2026, 9:36 p.m. |
| PDg | Predicate description generation | batch_69c0623e3cd48190929b0e3cba013909 |
completed | March 22, 2026, 9:42 p.m. |
Created at: March 22, 2026, 4:46 p.m.