Triple
T37730862
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sir Thomas Temple, 1st Baronet of Stowe |
E940148
|
entity |
| Predicate | nobleTitle |
P914
|
FINISHED |
| Object |
1st Baronet of Stowe
1st Baronet of Stowe is a hereditary baronetcy in the Baronetage of England associated with the Temple family estate at Stowe.
|
E2241125
|
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: 1st Baronet of Stowe | Statement: [Sir Thomas Temple, 1st Baronet of Stowe, nobleTitle, 1st Baronet of Stowe]
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: 1st Baronet of Stowe Triple: [Sir Thomas Temple, 1st Baronet of Stowe, nobleTitle, 1st Baronet of Stowe]
Generated description
1st Baronet of Stowe is a hereditary baronetcy in the Baronetage of England associated with the Temple family estate at Stowe.
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_69f76edefd048190a32212c5c3919531 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbae9585908190883eae74bb9631a1 |
completed | May 6, 2026, 9:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a40d6839b408190b89f88b9ab96a4f7 |
completed | June 28, 2026, 8:08 a.m. |
| NEDg | Description generation | batch_6a40d80217c8819092dc57b0444005b5 |
completed | June 28, 2026, 8:14 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a40da184e948190a2a014246d5b4ca5 |
completed | June 28, 2026, 8:23 a.m. |
Created at: May 3, 2026, 4:18 p.m.