Triple
T24458
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harry S. Truman |
E487
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Harry |
E487
|
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: Harry | Statement: [Harry S. Truman, givenName, Harry]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Harry Context triple: [Harry S. Truman, givenName, Harry]
-
A.
Harry
chosen
Harry is the given name of Harry S. Truman, the 33rd president of the United States who led the country through the end of World War II and the beginning of the Cold War.
-
B.
Robert
Robert is a common masculine given name of Germanic origin, widely used in English-speaking countries.
-
C.
Henry
Henry is the given name of Henry A. Kissinger, the influential American diplomat and political scientist who served as U.S. Secretary of State and National Security Advisor.
-
D.
Harold
Harold is a masculine given name of Old English origin, historically borne by several notable figures including kings and modern public personalities.
-
E.
Albert
Albert is the given name of the renowned theoretical physicist Albert Einstein, whose work revolutionized modern physics.
- 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_69a243b4ac2c8190b93c303df797b7b2 |
completed | Feb. 28, 2026, 1:24 a.m. |
| NER | Named-entity recognition | batch_69a2466d166881908bd8513c8d09fe8d |
completed | Feb. 28, 2026, 1:35 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a29817d9d08190aea256b0fbbb2d9b |
completed | Feb. 28, 2026, 7:24 a.m. |
Created at: Feb. 28, 2026, 1:34 a.m.