Triple
T4837722
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Akhmim |
E108101
|
entity |
| Predicate | hasLanguageUsedHistorically |
P1434
|
FINISHED |
| Object | Ancient Egyptian |
—
|
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: Ancient Egyptian | Statement: [Akhmim, hasLanguageUsedHistorically, Ancient Egyptian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLanguageUsedHistorically Context triple: [Akhmim, hasLanguageUsedHistorically, Ancient Egyptian]
-
A.
hasMajorityLanguageHistorically
Indicates that a particular language has historically been the predominant or majority language within a given entity or region.
-
B.
historicallySpokenIn
chosen
Indicates that a language was used for spoken communication in a particular place or region during a past historical period.
-
C.
historicalLanguage
Indicates that one language is a historical or earlier form/ancestor of another language.
-
D.
historicalLanguageStatus
Indicates that a language had a particular official, social, or functional status during a past historical period.
-
E.
historicalLanguageFeature
Indicates that a language possesses a feature, trait, or characteristic that existed or was relevant in a past historical period.
- 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_69bd43fbe444819085cb970706ef73f7 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ff981fc819080d4466c6fe06cf3 |
completed | March 20, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69bd6c21c7f08190846049d31fdfa144 |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:25 p.m.