Triple

T35797085
Position Surface form Disambiguated ID Type / Status
Subject Hili Archaeological Park E1034864 entity
Predicate partOf P40 FINISHED
Object Hili area
Hili area is a region in Al Ain, United Arab Emirates, known for its Bronze Age archaeological sites and ancient settlements.
E2157828 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: Hili area | Statement: [Hili Archaeological Park, partOf, Hili area]
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: Hili area
Triple: [Hili Archaeological Park, partOf, Hili area]
Generated description
Hili area is a region in Al Ain, United Arab Emirates, known for its Bronze Age archaeological sites and ancient settlements.

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_69f76e169bd081909f16cd8c9ee7870c completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7a25600d48190a3b8197343038068 completed May 3, 2026, 7:30 p.m.
NED1 Entity disambiguation (via context triple) batch_6a389c117c4481908049ed51789c3552 completed June 22, 2026, 2:21 a.m.
NEDg Description generation batch_6a389cc7b01c8190a8a2b7645b007f6c completed June 22, 2026, 2:24 a.m.
NED2 Entity disambiguation (via description) batch_6a389d9dcbd88190b86408dcb14f8128 completed June 22, 2026, 2:27 a.m.
Created at: May 3, 2026, 4:06 p.m.