Triple
T35329870
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Auto-Owners Insurance |
E1020288
|
entity |
| Predicate | hasNumberOfAgents |
P48532
|
FINISHED |
| Object | thousands of independent agents (approximate) |
—
|
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: thousands of independent agents (approximate) | Statement: [Auto-Owners Insurance, hasNumberOfAgents, thousands of independent agents (approximate)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfAgents Context triple: [Auto-Owners Insurance, hasNumberOfAgents, thousands of independent agents (approximate)]
-
A.
numberOfAgents
chosen
Indicates the quantity of agents involved in or associated with a given entity or situation.
-
B.
hasNumberOfAgencies
Indicates the quantity of agencies associated with or linked to a given entity.
-
C.
hasAgent
Indicates that an action or event is carried out or initiated by a particular agent.
-
D.
hasOpposingAgent
Indicates that an entity is opposed or counteracted by another agent in a given context or interaction.
-
E.
hasNumberOfAssailants
Indicates the relationship specifying how many assailants are involved in a given event or situation.
- 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_69f76deacf4481908e7735a5a7715b0a |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fedd5a5f4c8190acce88db56303703 |
completed | May 9, 2026, 7:08 a.m. |
| PD | Predicate disambiguation | batch_69fed910b31c8190ae837163d146738d |
completed | May 9, 2026, 6:49 a.m. |
Created at: May 3, 2026, 4:03 p.m.