Triple
T3797118
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mohammad Najibullah |
E91598
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object | Gardez |
E258256
|
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: Gardez | Statement: [Mohammad Najibullah, placeOfBirth, Gardez]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gardez Context triple: [Mohammad Najibullah, placeOfBirth, Gardez]
-
A.
Gardez
chosen
Gardez is a city in eastern Afghanistan that serves as the capital of Paktia Province and an important regional administrative and commercial center.
-
B.
Garde
Garde is the surname of American stage, film, and radio actress Betty Garde, known for her character roles in mid-20th-century entertainment.
-
C.
Guarda
Guarda is a historic city in central Portugal known for being the country's highest-altitude city and for its well-preserved medieval architecture.
-
D.
Heed
Heed is the fiercely loyal yet conflicted protagonist of Toni Morrison’s novel "Love," whose lifelong bond and rivalry with her friend Christine drive much of the story’s emotional and thematic tension.
-
E.
Garding
Garding is a small town in the Nordfriesland district of Schleswig-Holstein in northern Germany.
- 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_69aed96354f48190a768966d6bd19b04 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aee7a0818481909460197929ebb8e4 |
completed | March 9, 2026, 3:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4f061a9e481908d16ae0aa44e2f16 |
completed | March 14, 2026, 5:21 a.m. |
Created at: March 9, 2026, 3:15 p.m.