Triple
T866560
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Best Companies to Work For |
E18714
|
entity |
| Predicate | oftenSegmentedBy |
P12217
|
FINISHED |
| Object | industry |
—
|
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: industry | Statement: [Best Companies to Work For, oftenSegmentedBy, industry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oftenSegmentedBy Context triple: [Best Companies to Work For, oftenSegmentedBy, industry]
-
A.
dividedBetween
Indicates that something is partitioned or shared among two or more distinct entities or groups.
-
B.
separates
Indicates that one entity divides, parts, or keeps other entities apart from each other.
-
C.
separatedInto
chosen
Indicates that something has been divided or split into distinct parts, groups, or components.
-
D.
typicalSegmentType
Indicates that something is classified as belonging to a usual or characteristic type of segment within a broader structure or sequence.
-
E.
oftenCrossedOn
Indicates that one entity is frequently traversed or passed over by another entity.
- 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_69a4938ce8688190a24bdfef82ba7d21 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ac7cb1888190a46c16b30256451b |
completed | March 1, 2026, 9:15 p.m. |
| PD | Predicate disambiguation | batch_69a4aa87504481909618a6815948da6f |
completed | March 1, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:39 p.m.