Triple
T30239906
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ramkumar Ganesan |
E768879
|
entity |
| Predicate | hasRelativeInIndustry |
P110506
|
FINISHED |
| Object | Prabhu (Tamil actor) |
—
|
NE NERFINISHED |
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: Prabhu (Tamil actor) | Statement: [Ramkumar Ganesan, hasRelativeInIndustry, Prabhu (Tamil actor)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRelativeInIndustry Context triple: [Ramkumar Ganesan, hasRelativeInIndustry, Prabhu (Tamil actor)]
-
A.
hasRelativeInSameIndustry
chosen
Indicates that one entity has a relative who works in the same industry as the entity.
-
B.
relationToIndustry
Indicates how an entity is connected or relevant to a particular industry, such as through involvement, impact, or association.
-
C.
containsIndustry
Indicates that one entity includes or encompasses a particular industry within its scope, structure, or operations.
-
D.
hasPrincipalIndustry
Indicates that an entity’s main or primary industry of operation is the specified industry.
-
E.
isPartOfIndustry
Indicates that one entity belongs to, operates within, or is categorized under a particular industry sector.
- 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_69f224820c048190b1435c4cc145acf1 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_6a005d878aec81908e1177914a8fb610 |
completed | May 10, 2026, 10:27 a.m. |
| PD | Predicate disambiguation | batch_6a005c382f8881908ff33ebb7f88c430 |
completed | May 10, 2026, 10:21 a.m. |
Created at: April 29, 2026, 7:38 p.m.