Triple
T34816178
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Magha Mela |
E1003641
|
entity |
| Predicate | hasTemporarySettlement |
P135066
|
FINISHED |
| Object | tented city |
—
|
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: tented city | Statement: [Magha Mela, hasTemporarySettlement, tented city]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTemporarySettlement Context triple: [Magha Mela, hasTemporarySettlement, tented city]
-
A.
consideredTemporarySettlementOf
Indicates that one location is regarded as a provisional or non-permanent settlement associated with another place.
-
B.
hasSubsettlement
Indicates that one settlement includes another, smaller settlement as a subordinate or component part.
-
C.
hasSettlementAround
Indicates that a settlement is located in the surrounding area of a specified place or feature.
-
D.
temporarySettlementType
chosen
Indicates the type or category of a settlement that is intended to exist only temporarily rather than permanently.
-
E.
isSettlement
Indicates that the subject entity functions as a human-inhabited place or community, such as a town, village, or city.
- 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_69f76db717088190811b4e744610f37d |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69fe189fec148190aeef51b417ba15b0 |
completed | May 8, 2026, 5:08 p.m. |
| PD | Predicate disambiguation | batch_69fe17285b0881908de7569d8dbd20bd |
completed | May 8, 2026, 5:02 p.m. |
Created at: May 3, 2026, 3:59 p.m.