Triple
T8191235
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Irving Kahn |
E191311
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Irving |
E306850
|
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: Irving | Statement: [Irving Kahn, givenName, Irving]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Irving Context triple: [Irving Kahn, givenName, Irving]
-
A.
Irving
chosen
Irving is a masculine given name of English origin that gained prominence in the late 19th and early 20th centuries, borne by figures such as film producer Irving Thalberg and writer Washington Irving.
-
B.
Irving
Irving is a surname most famously associated with Washington Irving, the early 19th-century American author of classics like "Rip Van Winkle" and "The Legend of Sleepy Hollow."
-
C.
Irving
Irving is a major suburban city in the Dallas–Fort Worth metropolitan area known for its diverse population and significant business and transportation hubs.
-
D.
Irving, Texas
Irving, Texas is a major city in the Dallas–Fort Worth metropolitan area known for its corporate presence, transportation hubs, and role as a center for business and sports administration.
-
E.
Grand Tyler
Grand Tyler is a Masonic lodge officer responsible for guarding the entrance to the lodge and ensuring only duly qualified members are admitted.
- 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_69ca82c5b6948190a583c096fb0a6c71 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb4da4a6f08190be8088a28d928341 |
completed | March 31, 2026, 4:29 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cced979d408190851088c6d3f4df24 |
completed | April 1, 2026, 10:04 a.m. |
Created at: March 30, 2026, 5:42 p.m.