Triple
T6225296
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | J. P. Morgan |
E139215
|
entity |
| Predicate | hasMiddleName |
P143
|
FINISHED |
| Object | Pierpont |
E139215
|
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: Pierpont | Statement: [J. P. Morgan, hasMiddleName, Pierpont]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pierpont Context triple: [J. P. Morgan, hasMiddleName, Pierpont]
-
A.
Pierpont
chosen
Pierpont is the distinctive middle name of the influential American financier and banker J. P. Morgan.
-
B.
Pierrepont
Pierrepont is a given name associated with the American architect C. P. H. Gilbert, known for designing opulent Gilded Age mansions in New York City.
-
C.
Boughton
Boughton is a small rural village in Norfolk, England, situated near the settlement of Stoke Ferry.
-
D.
Pomeroy
Pomeroy is a small village in County Tyrone, Northern Ireland, known for its rural setting and surrounding upland landscapes.
-
E.
Mount Pleasant
Mount Pleasant is a historic, culturally diverse residential neighborhood in Washington, D.C., known for its tree-lined streets, early 20th-century row houses, and vibrant local commerce.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69c008afd3148190b71e9eaa60420dd1 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c062d42c688190be4d8d8325d6daaa |
completed | March 22, 2026, 9:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c20dd3dc5c8190bf48da3a90863727 |
completed | March 24, 2026, 4:06 a.m. |
Created at: March 22, 2026, 4:22 p.m.