Triple
T19991567
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Indian economy |
E494075
|
entity |
| Predicate | employmentCharacteristic |
P138237
|
FINISHED |
| Object | large informal sector |
—
|
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: large informal sector | Statement: [Indian economy, employmentCharacteristic, large informal sector]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: employmentCharacteristic Context triple: [Indian economy, employmentCharacteristic, large informal sector]
-
A.
commonEmployment
Indicates that two or more entities share the same employer or have worked for the same organization.
-
B.
employmentType
Indicates the specific kind or category of employment relationship that exists between an individual and an employer (e.g., full-time, part-time, contract).
-
C.
employment
Indicates a relationship where one entity hires, contracts, or otherwise engages another to perform work or services, typically in exchange for compensation.
-
D.
employmentContext
Indicates the situational or organizational setting in which an employment relationship or work activity takes place.
-
E.
professionAttribute
Indicates that a specific attribute, quality, or characteristic is associated with a given profession.
- F. None of above. chosen
Provenance (4 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_69da626a67648190af9653832a3aeced |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e65fe00b908190bda6b9a3a3281ec0 |
completed | April 20, 2026, 5:18 p.m. |
| PD | Predicate disambiguation | batch_69e537fd311881908448f2aea8b4812e |
completed | April 19, 2026, 8:15 p.m. |
| PDg | Predicate description generation | batch_69e543c42c688190a22f4d31ec692377 |
completed | April 19, 2026, 9:06 p.m. |
Created at: April 11, 2026, 3:31 p.m.