Triple

T2967015
Position Surface form Disambiguated ID Type / Status
Subject Shechem E80189 entity
Predicate associatedRuler P2830 FINISHED
Object Labayu
Labayu was a 14th-century BCE Canaanite ruler known from the Amarna letters for his aggressive expansionism and conflicts with neighboring city-states.
 E314801 NE FINISHED

How this triple was built (4 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: Labayu | Statement: [Shechem, associatedRuler, Labayu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Labayu
Context triple: [Shechem, associatedRuler, Labayu]
  • A. Tadlac
    Tadlac is a barangay in the municipality of Los Baños in Laguna province, Philippines, known for its proximity to Tadlac Lake (also called Alligator Lake).
  • B. Guaduas
    Guaduas is a historic town and municipality in the Cundinamarca Department of Colombia, known for its colonial architecture and role in the country’s independence era.
  • C. Moura
    Moura is a historic town in Portugal’s Alentejo region, known for its whitewashed architecture, olive oil production, and proximity to the Alqueva reservoir.
  • D. Soatá
    Soatá is a small town and municipality in the Boyacá Department of Colombia, known for its dry canyon landscapes and production of regional fruits.
  • E. Bassa
    Bassa is a Bantu language spoken primarily by the Bassa people of Cameroon and neighboring regions.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Labayu
Triple: [Shechem, associatedRuler, Labayu]
Generated description
Labayu was a 14th-century BCE Canaanite ruler known from the Amarna letters for his aggressive expansionism and conflicts with neighboring city-states.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Labayu
Target entity description: Labayu was a 14th-century BCE Canaanite ruler known from the Amarna letters for his aggressive expansionism and conflicts with neighboring city-states.
  • A. Tadlac
    Tadlac is a barangay in the municipality of Los Baños in Laguna province, Philippines, known for its proximity to Tadlac Lake (also called Alligator Lake).
  • B. Guaduas
    Guaduas is a historic town and municipality in the Cundinamarca Department of Colombia, known for its colonial architecture and role in the country’s independence era.
  • C. Moura
    Moura is a historic town in Portugal’s Alentejo region, known for its whitewashed architecture, olive oil production, and proximity to the Alqueva reservoir.
  • D. Soatá
    Soatá is a small town and municipality in the Boyacá Department of Colombia, known for its dry canyon landscapes and production of regional fruits.
  • E. Bassa
    Bassa is a Bantu language spoken primarily by the Bassa people of Cameroon and neighboring regions.
  • F. None of above. chosen

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_69ad8b1341848190bd19dbf46892887d completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad996e93788190ba9883714d4dfa0c completed March 8, 2026, 3:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69b0fc9fcfa48190a5e23ec1f3f01038 completed March 11, 2026, 5:24 a.m.
NEDg Description generation batch_69b100c1bfd48190ab71f460afb096e3 completed March 11, 2026, 5:42 a.m.
NED2 Entity disambiguation (via description) batch_69b10126bd788190b40f3ce1a8a547aa completed March 11, 2026, 5:44 a.m.
Created at: March 8, 2026, 2:58 p.m.