Triple
T31789953
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Figg and Muller Engineers |
E811434
|
entity |
| Predicate | hasNotableProjectState |
P51910
|
FINISHED |
| Object | North Carolina |
—
|
NE NERFINISHED |
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: North Carolina | Statement: [Figg and Muller Engineers, hasNotableProjectState, North Carolina]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableProjectState Context triple: [Figg and Muller Engineers, hasNotableProjectState, North Carolina]
-
A.
hasNotableProject
Indicates that an entity is associated with a project that is distinguished or recognized as significant in some way.
-
B.
hasProject
Indicates that an entity is associated with or responsible for a particular project.
-
C.
hasNotableProjectLocation
Indicates that an entity has a significant or noteworthy project situated at a particular location.
-
D.
hasNotableWorkSetThere
Indicates that a notable work (such as a book, film, or other creative piece) is set in or takes place within the referenced location.
-
E.
hasProjectIn
chosen
Indicates that an entity is involved with or associated with a project that takes place within a specified location or context.
- 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_69f348e60748819082dcaa7792659803 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_6a00bb3a6f888190b3ecd0fbc9af9b4a |
completed | May 10, 2026, 5:07 p.m. |
| PD | Predicate disambiguation | batch_6a00b902dbf881909e098ff102b7ea7e |
completed | May 10, 2026, 4:57 p.m. |
Created at: April 30, 2026, 11:38 p.m.