Triple
T14146896
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Loews Corporation |
E350573
|
entity |
| Predicate | hasPrimaryBusinessArea |
P70059
|
FINISHED |
| Object | property and casualty insurance |
—
|
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: property and casualty insurance | Statement: [Loews Corporation, hasPrimaryBusinessArea, property and casualty insurance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrimaryBusinessArea Context triple: [Loews Corporation, hasPrimaryBusinessArea, property and casualty insurance]
-
A.
primaryBusinessArea
chosen
Indicates the main field, sector, or domain in which an entity primarily conducts its business activities.
-
B.
hasPrimaryBusinessLocation
Indicates that an entity’s main or principal place of business is located at a specified location.
-
C.
hasKeyBusinessArea
Indicates that an entity is associated with or operates within a particular primary business area or domain.
-
D.
hasPrimaryServiceArea
Indicates that an entity is associated with a main geographic or functional area in which it primarily provides its services.
-
E.
isPartOfBusinessArea
Indicates that one entity belongs to, is included within, or falls under the scope of a particular business area.
- 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_69d827865f608190b311820428ae027b |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de612266248190a8591b646fe30ae6 |
completed | April 14, 2026, 3:45 p.m. |
| PD | Predicate disambiguation | batch_69de05b8434c81908c33b1b513463b12 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 10, 2026, 12:54 a.m.