Triple
T3947170
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Statue of Mahatma Gandhi, Parliament Square |
E92173
|
entity |
| Predicate | subjectReligion |
P52189
|
FINISHED |
| Object | Hinduism |
—
|
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: Hinduism | Statement: [Statue of Mahatma Gandhi, Parliament Square, subjectReligion, Hinduism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subjectReligion Context triple: [Statue of Mahatma Gandhi, Parliament Square, subjectReligion, Hinduism]
-
A.
religiousTopicAddressed
Indicates that a subject deals with, discusses, or focuses on a religious theme, issue, or question.
-
B.
laterReligion
Indicates that one religion or religious affiliation chronologically follows or replaces another for the same entity.
-
C.
bearerReligion
Indicates that a bearer (such as a person or entity) adheres to, practices, or is associated with a particular religion.
-
D.
religiousTarget
Indicates that an action, policy, or behavior is directed at someone or something specifically because of their religion or religious affiliation.
-
E.
religionCommon
Indicates that the related entities share the same religion or religious affiliation.
- 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_69aed965502c8190904ebad1203a4ae8 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef1515c688190a38332aedeed8a76 |
completed | March 9, 2026, 4:12 p.m. |
| PD | Predicate disambiguation | batch_69aee764235081909309b3c982f322a9 |
completed | March 9, 2026, 3:29 p.m. |
| PDg | Predicate description generation | batch_69aef14f9bb4819098e64b527b546d74 |
completed | March 9, 2026, 4:11 p.m. |
Created at: March 9, 2026, 3:24 p.m.