Triple
T23035892
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FMS Delhi |
E573592
|
entity |
| Predicate | placementCharacteristic |
P128001
|
FINISHED |
| Object | strong recruitment from consulting firms |
—
|
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: strong recruitment from consulting firms | Statement: [FMS Delhi, placementCharacteristic, strong recruitment from consulting firms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: placementCharacteristic Context triple: [FMS Delhi, placementCharacteristic, strong recruitment from consulting firms]
-
A.
entityCharacteristic
chosen
Indicates that an entity possesses, exhibits, or is defined by a particular characteristic or attribute.
-
B.
laborForceCharacteristic
Indicates a relationship where an entity is described or classified by a specific attribute or status related to its participation in the labor force.
-
C.
densityCharacteristic
Indicates that one entity specifies or characterizes the density property or density-related attribute of another entity.
-
D.
domainCharacteristic
Indicates that a domain or area of interest possesses a particular characteristic or defining property.
-
E.
placementType
Indicates the specific manner or category in which something is positioned, arranged, or assigned within a given context.
- 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_69e245b911188190bc3d96326c847969 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1850df7fc81909ee522d99d96af0d |
completed | April 29, 2026, 4:11 a.m. |
| PD | Predicate disambiguation | batch_69ef3ba004a48190885aece88efd1f52 |
completed | April 27, 2026, 10:34 a.m. |
Created at: April 17, 2026, 3:53 p.m.