Triple
T6423015
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kiewit Constructors |
E127989
|
entity |
| Predicate | hasSafetyFocus |
P32502
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Kiewit Constructors, hasSafetyFocus, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSafetyFocus Context triple: [Kiewit Constructors, hasSafetyFocus, yes]
-
A.
hasSafetyCharacteristic
Indicates that an entity possesses a specific safety-related property, feature, or attribute.
-
B.
safetyRelevant
Indicates that the associated entity, condition, or information has a direct impact on safety or is critical for preventing harm or accidents.
-
C.
notableSafety
chosen
Indicates that an entity is recognized for having significant safety characteristics, performance, or impact relative to others.
-
D.
safetyGoal
Indicates that an entity is associated with a specific safety objective or target condition intended to prevent harm or reduce risk.
-
E.
hasSafetyCertificate
Indicates that an entity possesses or has been granted a valid safety certificate.
- 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_69c00838de888190af2eec0b80495efa |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0690576c48190b5db5464eacc9de3 |
completed | March 22, 2026, 10:11 p.m. |
| PD | Predicate disambiguation | batch_69c060f780b08190aa650b4d1fc51f21 |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:43 p.m.