Triple
T9436962
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ermont |
E227534
|
entity |
| Predicate | belongsToDepartmentNumber |
P9698
|
FINISHED |
| Object | 95 |
—
|
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: 95 | Statement: [Ermont, belongsToDepartmentNumber, 95]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: belongsToDepartmentNumber Context triple: [Ermont, belongsToDepartmentNumber, 95]
-
A.
belongsToDivision
Indicates that an entity is a member of, or is organizationally assigned to, a specific division.
-
B.
worksInDepartment
Indicates that an entity is employed in and performs their job duties within a particular department.
-
C.
departmentNumber
chosen
Indicates the specific numeric code assigned to identify a particular department within an organization or system.
-
D.
belongsToDepartmentCapitalRegion
Indicates that an entity is part of, or administratively assigned to, the capital region of a department.
-
E.
hasDepartmentSeatRole
Indicates that an entity holds a specific role or position associated with a seat in a particular department.
- 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_69ca8437a7ac81908651de48f2d2141d |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd7ede1e148190b5793863a851c92c |
completed | April 1, 2026, 8:23 p.m. |
| PD | Predicate disambiguation | batch_69cca55548488190b171ae695a3212de |
completed | April 1, 2026, 4:55 a.m. |
Created at: March 30, 2026, 7:50 p.m.