Triple

T37313605
Position Surface form Disambiguated ID Type / Status
Subject Wadala E926270 entity
Predicate hasLandmark P105 FINISHED
Object Wadala Salt Pans
Wadala Salt Pans are expansive coastal salt fields in Mumbai historically used for salt production and now notable as a distinctive open landscape amid the city’s urban development.
E2221883 NE 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: Wadala Salt Pans | Statement: [Wadala, hasLandmark, Wadala Salt Pans]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Wadala Salt Pans
Triple: [Wadala, hasLandmark, Wadala Salt Pans]
Generated description
Wadala Salt Pans are expansive coastal salt fields in Mumbai historically used for salt production and now notable as a distinctive open landscape amid the city’s urban development.

Provenance (5 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_69f76eb28af88190b093b32e3fd614ab completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fb5b39606481908480a2ddf867ecce completed May 6, 2026, 3:16 p.m.
NED1 Entity disambiguation (via context triple) batch_6a40639501a481909402aa7c7427f92d completed June 27, 2026, 11:58 p.m.
NEDg Description generation batch_6a4064b46ae48190b0949d72795badd6 completed June 28, 2026, 12:03 a.m.
NED2 Entity disambiguation (via description) batch_6a40651995508190a458b790a90bd3aa completed June 28, 2026, 12:04 a.m.
Created at: May 3, 2026, 4:16 p.m.