Triple

T23935034
Position Surface form Disambiguated ID Type / Status
Subject Battle against Sisera E602608 entity
Predicate hasAssociatedPlace P19735 FINISHED
Object Harosheth Haggoyim
Harosheth Haggoyim was an ancient Canaanite stronghold and base of operations for the commander Sisera, mentioned in the biblical Book of Judges.
E1610947 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: Harosheth Haggoyim | Statement: [Battle against Sisera, hasAssociatedPlace, Harosheth Haggoyim]
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: Harosheth Haggoyim
Triple: [Battle against Sisera, hasAssociatedPlace, Harosheth Haggoyim]
Generated description
Harosheth Haggoyim was an ancient Canaanite stronghold and base of operations for the commander Sisera, mentioned in the biblical Book of Judges.

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_69e2953cf6e081909b8e25a10a52dddc completed April 17, 2026, 8:17 p.m.
NER Named-entity recognition batch_69f1cf9e8abc8190a3028a358265912e completed April 29, 2026, 9:30 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f764728e88190b084674692ca2002 completed May 21, 2026, 9:16 p.m.
NEDg Description generation batch_6a0f76f2b5248190b92095f8003001be completed May 21, 2026, 9:19 p.m.
NED2 Entity disambiguation (via description) batch_6a0f78df8c9c81908eb3912b212862f9 completed May 21, 2026, 9:27 p.m.
Created at: April 17, 2026, 9:01 p.m.