Triple
T6534609
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Netaji Nagar Beach |
E152322
|
entity |
| Predicate | isRelatively |
P71486
|
FINISHED |
| Object | less crowded |
—
|
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: less crowded | Statement: [Netaji Nagar Beach, isRelatively, less crowded]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isRelatively Context triple: [Netaji Nagar Beach, isRelatively, less crowded]
-
A.
hasRelativeLocation
Indicates that one entity is positioned in space in relation to another entity’s location.
-
B.
relativeLength
Indicates a comparative relationship between entities based on how long they are relative to one another.
-
C.
relativePosition
Indicates the spatial relationship of one entity’s location with respect to another entity’s position.
-
D.
hasRelativeRole
Indicates that one entity holds a familial or kinship-based role in relation to another entity.
-
E.
hasRelativeRelief
Indicates a relationship where one entity is characterized by the degree of variation in elevation or relief relative to another reference entity or area.
- 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_69c688048ec8819093a47f7d332e12ec |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6adc05da88190b402085954cec8e0 |
completed | March 27, 2026, 4:18 p.m. |
| PD | Predicate disambiguation | batch_69c68abd9c7c819099e4fe8097cd1b28 |
completed | March 27, 2026, 1:48 p.m. |
| PDg | Predicate description generation | batch_69c69f362ee4819090e8fa48caef7d7d |
completed | March 27, 2026, 3:16 p.m. |
Created at: March 27, 2026, 1:46 p.m.