Triple
T20523606
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Martyr’s Column |
E503874
|
entity |
| Predicate | marksExactSpotOf |
P109072
|
FINISHED |
| Object | place where Mahatma Gandhi was shot |
—
|
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: place where Mahatma Gandhi was shot | Statement: [Martyr’s Column, marksExactSpotOf, place where Mahatma Gandhi was shot]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: marksExactSpotOf Context triple: [Martyr’s Column, marksExactSpotOf, place where Mahatma Gandhi was shot]
-
A.
marksLocationOf
chosen
Indicates that one entity serves as a marker, sign, or indicator specifying the location of another entity.
-
B.
locationOfMark
Indicates that one entity is the place or position where a particular mark is found or applied.
-
C.
marksMeetingPointOf
Indicates that something designates or identifies the specific location where two or more entities meet or converge.
-
D.
positionSpecific
Indicates that something applies only at, or is defined with respect to, a particular position or location within a larger structure or sequence.
-
E.
scarLocation
Indicates the anatomical location on an entity where a scar is present.
- 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_69e0b4b3a6e08190ae663701f50fab8e |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69f471f18819091e8a57161fe0225 |
completed | April 20, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69e59fdb7ad88190924176c32a195db3 |
completed | April 20, 2026, 3:39 a.m. |
Created at: April 16, 2026, 11:36 a.m.