Triple

T25629624
Position Surface form Disambiguated ID Type / Status
Subject University of Pennsylvania Tikal Project E642535 entity
Predicate directedBy P7373 FINISHED
Object William R. Coe
William R. Coe was an American archaeologist best known for his leading role in the excavation and study of the ancient Maya city of Tikal.
E2295072 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: William R. Coe | Statement: [University of Pennsylvania Tikal Project, directedBy, William R. Coe]
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: William R. Coe
Triple: [University of Pennsylvania Tikal Project, directedBy, William R. Coe]
Generated description
William R. Coe was an American archaeologist best known for his leading role in the excavation and study of the ancient Maya city of Tikal.

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_69e77e7bd4548190a0c691b8a2f27ff1 completed April 21, 2026, 1:41 p.m.
NER Named-entity recognition batch_69f5fa260734819080d7d32c6912d267 completed May 2, 2026, 1:20 p.m.
NED1 Entity disambiguation (via context triple) batch_6a7d02b8c7a081909e6a4734178fa14b completed Aug. 12, 2026, 11:33 p.m.
NEDg Description generation batch_6a7d033d39208190a9d3c7a87a179142 completed Aug. 12, 2026, 11:35 p.m.
NED2 Entity disambiguation (via description) batch_6a7d0425b91c819087b2211f395e378a completed Aug. 12, 2026, 11:39 p.m.
Created at: April 21, 2026, 5:17 p.m.