Triple
T17357507
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MCCSSS |
E421976
|
entity |
| Predicate | hasSpecialtyArea |
P466
|
FINISHED |
| Object | supply |
—
|
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: supply | Statement: [MCCSSS, hasSpecialtyArea, supply]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpecialtyArea Context triple: [MCCSSS, hasSpecialtyArea, supply]
-
A.
hasSpecialty
chosen
Indicates that an entity possesses a particular area of expertise, focus, or professional specialization.
-
B.
hasSpecialist
Indicates that one entity is associated with or assigned to a specialist entity that provides expert support, service, or oversight for it.
-
C.
hasSpecialistStatus
Indicates that an entity holds a recognized specialist designation or status in a particular field, role, or context.
-
D.
hasSpecialtyChannel
Indicates that one entity provides or is associated with a dedicated channel focused on a particular specialty or subject area for another entity.
-
E.
hasResearchArea
Indicates that an entity (such as a person, project, or organization) is associated with or focused on a particular field or area of research.
- 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_69d889d520008190a26917a95bf1c2ea |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43a4976788190b00c00f710be6c46 |
completed | April 19, 2026, 2:13 a.m. |
| PD | Predicate disambiguation | batch_69e3b02662d08190a07d0fb5c04b6f33 |
completed | April 18, 2026, 4:24 p.m. |
Created at: April 10, 2026, 5:44 a.m.