Triple
T7722988
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | American-Marietta Corporation |
E175058
|
entity |
| Predicate | corporateEvent |
P46794
|
FINISHED |
| Object | merger leading to Martin Marietta |
—
|
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: merger leading to Martin Marietta | Statement: [American-Marietta Corporation, corporateEvent, merger leading to Martin Marietta]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: corporateEvent Context triple: [American-Marietta Corporation, corporateEvent, merger leading to Martin Marietta]
-
A.
associatedWithCorporateEvent
chosen
Indicates that an entity has a connection or involvement with a specific corporate event.
-
B.
eventManagement
Indicates the organization, coordination, and oversight of all activities and resources involved in planning and executing an event.
-
C.
organisedEvent
Indicates that an entity planned, coordinated, and carried out an event.
-
D.
eventTypeOrganized
Indicates that an entity organized or arranged a specific type or category of event.
-
E.
industryEvent
Indicates that an event is related to a specific industry, such as a conference, trade show, or professional gathering focused on that industry.
- 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_69c6995d541c81909eaa646b1a8369a9 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c7074eca4c8190bd51fd1b450729e8 |
completed | March 27, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69c7016a6cf88190b53bf4b958f0f302 |
completed | March 27, 2026, 10:15 p.m. |
Created at: March 27, 2026, 4:05 p.m.