Triple
T29714584
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Citizenship (Amendment) Act, 2003 |
E751873
|
entity |
| Predicate | tightenedProvision |
P167630
|
FINISHED |
| Object | citizenship by birth |
—
|
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: citizenship by birth | Statement: [Citizenship (Amendment) Act, 2003, tightenedProvision, citizenship by birth]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tightenedProvision Context triple: [Citizenship (Amendment) Act, 2003, tightenedProvision, citizenship by birth]
-
A.
tightens
Indicates that one entity makes another entity more secure, compact, or taut by applying constricting force or reducing looseness.
-
B.
tightFor
Indicates that one entity fits another with little or no extra space, suggesting a close or constraining fit.
-
C.
tightness
Indicates how closely or firmly two or more entities are bound, constrained, or fitted together in relation to each other.
-
D.
enforcedProvision
Indicates that an authority or agent compelled compliance with a specific rule, term, or provision.
-
E.
isTight
Indicates that one entity fits closely or securely around, against, or within another without looseness or extra space.
- 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_69f0d62748848190b030d0a703629a7d |
completed | April 28, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f672dc0c30819097ab601576f79454 |
completed | May 2, 2026, 9:55 p.m. |
| PD | Predicate disambiguation | batch_69f6659f246081909821c5f452d14e8f |
completed | May 2, 2026, 8:59 p.m. |
| PDg | Predicate description generation | batch_69f6691da93081909deaf680614fc900 |
completed | May 2, 2026, 9:14 p.m. |
Created at: April 28, 2026, 7:33 p.m.