Triple
T20634866
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GM Ramos Arizpe Plant |
E507049
|
entity |
| Predicate | hasShiftSystem |
P11916
|
FINISHED |
| Object | multi‑shift manufacturing operations |
—
|
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: multi‑shift manufacturing operations | Statement: [GM Ramos Arizpe Plant, hasShiftSystem, multi‑shift manufacturing operations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasShiftSystem Context triple: [GM Ramos Arizpe Plant, hasShiftSystem, multi‑shift manufacturing operations]
-
A.
hasDynamicShifts
Indicates that something exhibits changes or transitions in state, intensity, or behavior over time rather than remaining constant.
-
B.
hasShiftPressureFrom
Indicates that one entity experiences or is subjected to shift-related pressure originating from another entity.
-
C.
hasNumberOfShifts
chosen
Indicates the quantity of work shifts associated with a given entity.
-
D.
usesShiftCharacter
Indicates that an entity employs or requires the use of a shift (modifier) character, such as for capitalization or accessing alternate symbols.
-
E.
shiftsWhen
Indicates that one state, condition, or configuration changes to another under specified circumstances or triggers.
- 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_69e0b4bd4a0081908d4e97a590a33fb2 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6ad0e5fc481909e4f0dd7fb1203fc |
completed | April 20, 2026, 10:47 p.m. |
| PD | Predicate disambiguation | batch_69e5a0155bd48190b3c769a12cc2c83d |
completed | April 20, 2026, 3:40 a.m. |
Created at: April 16, 2026, 11:42 a.m.