Triple
T2570866
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Palestine Post |
E57661
|
entity |
| Predicate | usedLanguagesOnStamps |
P15804
|
FINISHED |
| Object | English |
—
|
LITERAL 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: English | Statement: [Palestine Post, usedLanguagesOnStamps, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedLanguagesOnStamps Context triple: [Palestine Post, usedLanguagesOnStamps, English]
-
A.
languageOnBanknotes
Indicates the language that is printed or used on a country's banknotes.
-
B.
emblemLanguage
Indicates that an emblem (such as a symbol or logo) is associated with or presented in a particular language.
-
C.
languageOfLetters
Indicates that one entity is the language in which the other entity’s letters or written correspondence are composed.
-
D.
inscriptionsLanguage
chosen
Indicates that the language used in the inscriptions on an object or surface is the specified language.
-
E.
officialLanguageOnFlag
Indicates that a particular language is officially represented in the text or inscriptions displayed on a flag.
- F. None of above.
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_69ab4a51410081908501dcf8bad9adc4 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd382928c8190b6316f3db48d8e73 |
completed | March 7, 2026, 7:28 a.m. |
| PD | Predicate disambiguation | batch_69abd0ce4dcc8190b17a65abf9bd1bb0 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:48 p.m.