Triple

T25120173
Position Surface form Disambiguated ID Type / Status
Subject Palenque sculptural style E629242 entity
Predicate hasExample P1259 FINISHED
Object Tablet of the 96 Glyphs
The Tablet of the 96 Glyphs is a finely carved Maya inscription panel from Palenque, renowned for its dense grid of hieroglyphs exemplifying the city’s elegant Classic-period sculptural and calligraphic style.
E1666467 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: Tablet of the 96 Glyphs | Statement: [Palenque sculptural style, hasExample, Tablet of the 96 Glyphs]
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: Tablet of the 96 Glyphs
Triple: [Palenque sculptural style, hasExample, Tablet of the 96 Glyphs]
Generated description
The Tablet of the 96 Glyphs is a finely carved Maya inscription panel from Palenque, renowned for its dense grid of hieroglyphs exemplifying the city’s elegant Classic-period sculptural and calligraphic style.

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_69e2ff3288048190bd82c3b7f7bd0e62 completed April 18, 2026, 3:49 a.m.
NER Named-entity recognition batch_69f465ca9a088190911a49d5117b67d8 completed May 1, 2026, 8:35 a.m.
NED1 Entity disambiguation (via context triple) batch_6a105cf6a4c08190a21b63f6537a2cdf completed May 22, 2026, 1:41 p.m.
NEDg Description generation batch_6a105dd12cd08190b382c57952107fa6 completed May 22, 2026, 1:44 p.m.
NED2 Entity disambiguation (via description) batch_6a105edf54888190a3b77f63eb867749 completed May 22, 2026, 1:49 p.m.
Created at: April 18, 2026, 6:28 a.m.