Triple
T27212565
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William Joel Bryan |
E684042
|
entity |
| Predicate | sibling |
P363
|
FINISHED |
| Object |
Moses Austin Bryan
Moses Austin Bryan was a 19th-century Texan pioneer and soldier who served in the Texas Revolution and helped preserve early Texas history.
|
E1761368
|
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: Moses Austin Bryan | Statement: [William Joel Bryan, sibling, Moses Austin Bryan]
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: Moses Austin Bryan Triple: [William Joel Bryan, sibling, Moses Austin Bryan]
Generated description
Moses Austin Bryan was a 19th-century Texan pioneer and soldier who served in the Texas Revolution and helped preserve early Texas history.
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_69eefad339a08190aeacb2a198f1a39b |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f62619db548190b38c77d51ea79fb3 |
completed | May 2, 2026, 4:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a1253a3b2b88190856eb94df30c7025 |
completed | May 24, 2026, 1:25 a.m. |
| NEDg | Description generation | batch_6a125455f8fc81909ae39b6651a0fdb0 |
completed | May 24, 2026, 1:28 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a12552837d88190a12496ca49423f0f |
completed | May 24, 2026, 1:32 a.m. |
Created at: April 27, 2026, 9:40 a.m.