Triple
T25456513
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | شيبة الحمد |
E637928
|
entity |
| Predicate | الاسم عند الصغر |
P158842
|
FINISHED |
| Object | شيبة الحمد |
—
|
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: شيبة الحمد | Statement: [شيبة الحمد, الاسم عند الصغر, شيبة الحمد]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: الاسم عند الصغر Context triple: [شيبة الحمد, الاسم عند الصغر, شيبة الحمد]
-
A.
الحفيد
Indicates a grandchild relationship, where one entity is the descendant (grandson or granddaughter) of another entity’s child.
-
B.
البنات
Indicates a relationship or action involving girls as the primary participants or subjects.
-
C.
البنت
Indicates a relationship where an entity is identified as a girl or daughter in relation to another entity.
-
D.
عدد الحروف
Indicates the relationship that specifies the number of letters contained in a given word or text.
-
E.
Xiaoerjing
Indicates a relationship where something is written, represented, or transcribed using the Xiaoerjing (Arabic-based) script for Sinitic languages.
- F. None of above. chosen
Provenance (4 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_69e75db8bab08190baca80b4a8c315fd |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5f72756748190aa315cc00882a798 |
completed | May 2, 2026, 1:07 p.m. |
| PD | Predicate disambiguation | batch_69f4806d93dc8190b9dff4c63186faff |
completed | May 1, 2026, 10:29 a.m. |
| PDg | Predicate description generation | batch_69f48b9058d081908ec9af261ee092e2 |
completed | May 1, 2026, 11:16 a.m. |
Created at: April 21, 2026, 2:10 p.m.