Triple
T199180
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ford family (controlling shareholders) |
E4063
|
entity |
| Predicate | sectorInfluence |
P8004
|
FINISHED |
| Object | U.S. manufacturing |
—
|
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: U.S. manufacturing | Statement: [Ford family (controlling shareholders), sectorInfluence, U.S. manufacturing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sectorInfluence Context triple: [Ford family (controlling shareholders), sectorInfluence, U.S. manufacturing]
-
A.
sector
Indicates that an entity operates in, belongs to, or is associated with a particular economic or industrial sector.
-
B.
sectorWeighting
Indicates the proportion or emphasis assigned to a particular sector within a broader portfolio, index, or classification.
-
C.
sectorServed
Indicates the industry or economic sector that an entity primarily serves or targets with its activities, products, or services.
-
D.
economicTrend
Indicates the general direction or pattern of economic activity or conditions over a period of time.
-
E.
economicAspect
Indicates that something is related to, characterized by, or has implications for economic factors, conditions, or outcomes.
- 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_69a254bca59881909a15e1496f1508c7 |
completed | Feb. 28, 2026, 2:36 a.m. |
| NER | Named-entity recognition | batch_69a25bcc6dc88190b8c24b485588dfe4 |
completed | Feb. 28, 2026, 3:06 a.m. |
| PD | Predicate disambiguation | batch_69a25b4886b48190b46fd2244648a098 |
completed | Feb. 28, 2026, 3:04 a.m. |
| PDg | Predicate description generation | batch_69a25bc6ba208190aa8bec59d32f95fd |
completed | Feb. 28, 2026, 3:06 a.m. |
Created at: Feb. 28, 2026, 2:44 a.m.