Triple
T37952851
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jordanian postal administration in the West Bank |
E946788
|
entity |
| Predicate | usedLanguageOnStamps |
P129578
|
FINISHED |
| Object | Arabic |
—
|
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: Arabic | Statement: [Jordanian postal administration in the West Bank, usedLanguageOnStamps, Arabic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedLanguageOnStamps Context triple: [Jordanian postal administration in the West Bank, usedLanguageOnStamps, Arabic]
-
A.
languageOnStamp
chosen
Indicates that a particular language appears on or is used in the text or inscriptions printed on a stamp.
-
B.
usedCurrencyOnStamps
Indicates that a particular currency was used as the denomination on a set of postage stamps.
-
C.
languageOnBanknotes
Indicates the language that is printed or used on a country's banknotes.
-
D.
officialLanguageOnEmblem
Indicates that a particular language is used as the official language displayed on an emblem, such as a coat of arms, seal, or flag.
-
E.
languageOfLetters
Indicates that one entity is the language in which the other entity’s letters or written correspondence are composed.
- 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_69f76ef64cf08190ad3e1114b62aac67 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbc7b78f9481909f4f8fc2e3fdcde1 |
completed | May 6, 2026, 10:59 p.m. |
| PD | Predicate disambiguation | batch_69fbbd18c9908190928d274f8731dfa8 |
completed | May 6, 2026, 10:13 p.m. |
Created at: May 3, 2026, 4:20 p.m.