Triple
T1968168
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Inequality-adjusted Human Development Index |
E42735
|
entity |
| Predicate | lossMeasure |
P8356
|
FINISHED |
| Object | difference between HDI and IHDI |
—
|
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: difference between HDI and IHDI | Statement: [Inequality-adjusted Human Development Index, lossMeasure, difference between HDI and IHDI]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lossMeasure Context triple: [Inequality-adjusted Human Development Index, lossMeasure, difference between HDI and IHDI]
-
A.
losses
chosen
Indicates that an entity experiences a decrease in value, quantity, or advantage as a result of some event or comparison.
-
B.
usesLossFunction
Indicates that one entity employs a particular loss function as part of its optimization or learning process.
-
C.
loserPoints
Indicates the number of points awarded to or accumulated by the losing side in a competitive event or comparison.
-
D.
loserScore
Indicates the number of points or score achieved by the losing participant in a competitive event or comparison.
-
E.
aimsToMeasure
Indicates that one entity is intended or designed to quantify, assess, or evaluate another entity or property.
- 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_69a88711151c8190940b2572095059d7 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb3d05cb88190963039d643bb6637 |
completed | March 7, 2026, 5:12 a.m. |
| PD | Predicate disambiguation | batch_69abaff7d4a48190ab0d51aefb1c4e31 |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:36 p.m.