Triple
T34103846
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DEA Albuquerque field office |
E874645
|
entity |
| Predicate | primaryWorkplaceOf |
P1527
|
FINISHED |
| Object | Hank Schrader |
E275833
|
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: Hank Schrader | Statement: [DEA Albuquerque field office, primaryWorkplaceOf, Hank Schrader]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryWorkplaceOf Context triple: [DEA Albuquerque field office, primaryWorkplaceOf, Hank Schrader]
-
A.
locationOfWork
chosen
Indicates the place or site where an entity performs its work or carries out its professional activities.
-
B.
primaryWork
Indicates that one work is the main or most significant work associated with a given entity, as opposed to other secondary or related works.
-
C.
professionalAddress
Indicates the formal title, name, and/or contact designation used to address someone in a professional or work-related context.
-
D.
workedPrimarilyIn
Indicates that an entity carried out the majority of its work, activity, or career within a particular field, location, or context.
-
E.
parentEmployer
Indicates that one organization is the direct or higher-level employer of another organization or entity.
- F. None of above.
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_69f349a80d4481908527317d43f5c579 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a037c8ae0248190b7e2ce4bf852c22d |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a376f86a3908190803a47787eb3bd0a |
completed | June 21, 2026, 4:58 a.m. |
| PD | Predicate disambiguation | batch_6a0379f963908190846d232f386fd98f |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:53 a.m.