Triple
T373686
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George F. Kennan |
E8323
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Long Telegram |
E2714
|
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: Long Telegram | Statement: [George F. Kennan, notableWork, Long Telegram]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Long Telegram Context triple: [George F. Kennan, notableWork, Long Telegram]
-
A.
Long Telegram
chosen
The Long Telegram was a 1946 diplomatic cable by U.S. diplomat George F. Kennan that laid the intellectual foundation for the Cold War strategy of containment against the Soviet Union.
-
B.
Long Gray Line
The Long Gray Line is the enduring collective of graduates of the United States Military Academy at West Point, symbolizing their shared traditions, service, and lifelong bond.
-
C.
Langer
Langer is a surname most notably associated with Robert Langer, a pioneering American chemical engineer and prolific inventor in biotechnology and drug delivery.
-
D.
Tglg
Tglg is the ISO 15924 script code assigned to the precolonial Philippine writing system Baybayin.
-
E.
ChatGPT Plus
ChatGPT Plus is a paid subscription tier of OpenAI’s ChatGPT service that offers enhanced access, faster performance, and priority use of advanced models compared to the free version.
- 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_69a2e7f2ec648190b42bc7db424f8109 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ec13b9b48190b294d998c6720132 |
completed | Feb. 28, 2026, 1:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3f0a9608481908bee4d83768e6497 |
completed | March 1, 2026, 7:54 a.m. |
Created at: Feb. 28, 2026, 1:08 p.m.