Triple
T10943438
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fayez Banihammad |
E258532
|
entity |
| Predicate | arrivalInUnitedStates |
P87280
|
FINISHED |
| Object | 2001-06-27 |
—
|
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: 2001-06-27 | Statement: [Fayez Banihammad, arrivalInUnitedStates, 2001-06-27]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: arrivalInUnitedStates Context triple: [Fayez Banihammad, arrivalInUnitedStates, 2001-06-27]
-
A.
entryToUnitedStatesDate
chosen
Indicates the date on which an entity entered the United States.
-
B.
dateOfPacificArrival
Indicates the date on which an entity arrived at a location on or in the Pacific region.
-
C.
legalStatusAtArrival
Indicates the legal status or classification an entity held at the time it first arrived at a particular place or jurisdiction.
-
D.
enteredCountry
Indicates that an entity has moved into or crossed the border to be physically present within a specified country.
-
E.
enteredUnitedStatesBeforeAttacks
Indicates that the subject entered the United States prior to the occurrence of the specified attacks.
- 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_69d6aa8769b4819082bfe5e61b9017f0 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d770c3fb388190a598f89ae59a7b51 |
completed | April 9, 2026, 9:26 a.m. |
| PD | Predicate disambiguation | batch_69d72e816a98819096d6c10dfb88a66a |
completed | April 9, 2026, 4:43 a.m. |
Created at: April 8, 2026, 9:23 p.m.